64 Crewai Jobs

Backend Engineer (Python, Node Js, Agentic AI) Exp : 3 - 7 yrs Location: Pune Min 3 yrs exp in Backend developer exposure to AI/ML Min 2+ yrs exp in backend development using Python and Node.js For JD, write to amit.gaine@talentxo.in

The role involves working on Agentic AI Platform Delivery where you will be responsible for developing and maintaining autonomous software agents using modern LLM frameworks. You will also be required to build reusable components for business process automation, design agent orchestration, prompt engineering, and LLM integrations, as well as enable deployment across CRM systems and enterprise data platforms. Additionally, you will work on Generative AI & Model Optimization by fine-tuning LLMs/SLMs with proprietary NBFC data, and focusing on model distillation, quantization, and edge deployment readiness. Moreover, you will be creating self-learning systems by developing adaptive frameworks that learn from interaction outcomes and implementing lightweight models to support real-time decision-making. The ideal candidate for this position should hold a B.E./B.Tech/M.Tech degree in Computer Science or a related field, with a minimum of 3-7 years of experience in AI/ML roles. Proficiency in languages such as Python, Node.JS, JavaScript, React, and Java is required, along with experience in using tools/frameworks like LangChain, Semantic Kernel, LangGraph, and CrewAI. Familiarity with platforms such as GCP, MS Foundry, Copilot Studio, BigQuery, and Power Apps/BI is essential. Knowledge of Agent Tools like Agent Development Kit (ADK) and Multi-agent Communication Protocol (MCP), as well as a strong understanding of prompt engineering, LLM integration, and orchestration, are also expected. In addition to the technical requirements, the candidate should possess strong communication skills, teamwork abilities, and problem-solving capabilities. Being proactive, detail-oriented, and able to work under pressure are desirable traits for this role. Joining this dynamic team at Bajaj Finance Limited offers numerous perks, benefits, and a vibrant work culture. The company values its employees and recognizes their contributions, making it a rewarding and challenging environment to grow and excel. With a presence in over 500 locations across India, you will have the opportunity to be part of one of Asia's top 10 Large workplaces and contribute to the success and innovation of a leading Non-banking financial company.,

#GenerativeAI Experts ready for AI race, this is for you! Announcing Hexaware conducting Walkin Drive for AI Engineer and Lead Data Scientist (GenAI)-Noida Location-3rd Aug 2025(Sunday) Interested candidates share your CV at umaparvathyc@hexaware.com Open Positions: AI Engineer/Lead Data Scientist (GenAI) AI Engineer Experience- 3+years Lead Data Scientist (GenAI) Experience- 7+years Notice Period- 15 days/30days Max (who serving Notice Period) Walkin Drive Location- Noida Date of drive- 3rd Aug 2025(Sunday) Must have Experience: LLM, Advance RAG, NLP, transformer model, LangChain Technical Skill: 1. Strong Experience in Data Scientist (GENAI) 2. Proficiency with Generative AI models like GANs, VAEs, and transformers 3. Expertise with cloud platforms (AWS, Azure, Google Cloud) for deploying AI models 4. Strong Python Fast API experience, SDA based implementations for all the APIs 5. Knowledge of Agentic AI concepts and applications

You will be part of a team that is building an Agentic AI Platform aimed at enabling enterprises to solve real business problems using Agentic AI workflows. The platform covers a wide range of areas from utility operations to legal document review. The ultimate goal is to empower AI agents to think, act, and deliver quickly, securely, and locally. As an Agentic AI Engineer, you will have the opportunity to work with cutting-edge frameworks such as Lang Chain, CrewAI, Lang Graph, Google ADK, and more. Your role will involve translating real enterprise challenges into intelligent multi-agent workflows. Your responsibilities will include building and deploying AI agents using open-source agentic frameworks, integrating models from sources like OpenAI, Mistral, Gemini, Llama, Claude, among others, and utilizing tools such as Retrieval-Augmented Generation (RAG), knowledge graphs, and vector stores. Collaboration with product managers and domain experts to address real problems in various enterprise domains like utilities, legal, marketing, and supply chain will be a key aspect of your role. Additionally, you will play a significant role in continuously testing and refining agent behavior and contributing to the enhancement of the proprietary DataInsightAI platform. To excel in this role, you should possess at least 1+ years of hands-on experience in implementing enterprise-level Gen AI projects that have been successfully deployed. Strong Python skills, familiarity with LLMs, agentic AI workflows, RAG, vector databases, and the ability to simplify complex problems are essential. A curiosity-driven mindset, a fast learner, and hands-on coding abilities are also crucial for success in this role. While not mandatory, experience in multi-agent architectures, graph databases like Neo4j, deployment on cloud platforms such as Azure/AWS/GCP, and familiarity with LangGraph or Google ADK are considered advantageous. Joining our team will offer you the opportunity to work on cutting-edge agentic AI projects daily, be part of a small team with significant ownership, ship solutions rapidly, and tackle real enterprise challenges. Moreover, you will be supported by InTimeTec, a company with a strong AI/ML engineering culture.,

You should have 3 to 10 years of experience in AI development and be located in Coimbatore. Immediate joiners are preferred. A minimum of 2 years of experience in core Gen AI is required. As an AI Developer, your responsibilities will include designing, developing, and fine-tuning Large Language Models (LLMs) for various in-house applications. You will implement and optimize Retrieval-Augmented Generation (RAG) techniques to enhance AI response quality. Additionally, you will develop and deploy Agentic AI systems capable of autonomous decision-making and task execution. Building and managing data pipelines for processing, transforming, and feeding structured/unstructured data into AI models will be part of your role. It is essential to ensure scalability, performance, and security of AI-driven solutions in production environments. Collaboration with cross-functional teams, including data engineers, software developers, and product managers, is expected. You will conduct experiments and evaluations to improve AI system accuracy and efficiency while staying updated with the latest advancements in AI/ML research, open-source models, and industry best practices. You should have strong experience in LLM fine-tuning using frameworks like Hugging Face, DeepSpeed, or LoRA/PEFT. Hands-on experience with RAG architectures, including vector databases such as Pinecone, ChromaDB, Weaviate, OpenSearch, and FAISS, is required. Experience in building AI agents using LangChain, LangGraph, CrewAI, AutoGPT, or similar frameworks is preferred. Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow is necessary. Experience in Python web frameworks such as FastAPI, Django, or Flask is expected. You should also have experience in designing and managing data pipelines using tools like Apache Airflow, Kafka, or Spark. Knowledge of cloud platforms (AWS/GCP/Azure) and containerization technologies (Docker, Kubernetes) is essential. Familiarity with LLM APIs (OpenAI, Anthropic, Mistral, Cohere, Llama, etc.) and their integration in applications is a plus. A strong understanding of vector search, embedding models, and hybrid retrieval techniques is required. Experience with optimizing inference and serving AI models in real-time production systems is beneficial. Experience with multi-modal AI (text, image, audio) and familiarity with privacy-preserving AI techniques and responsible AI frameworks are desirable. Understanding of MLOps best practices, including model versioning, monitoring, and deployment automation, is a plus. Skills required for this role include PyTorch, RAG architectures, OpenSearch, Weaviate, Docker, LLM fine-tuning, ChromaDB, Apache Airflow, LoRA, Python, hybrid retrieval techniques, Django, GCP, CrewAI, OpenAI, Hugging Face, Gen AI, Pinecone, FAISS, AWS, AutoGPT, embedding models, Flask, FastAPI, LLM APIs, DeepSpeed, vector search, PEFT, LangChain, Azure, Spark, Kubernetes, AI Gen, TensorFlow, real-time production systems, LangGraph, and Kafka.,

As a Senior Generative AI Engineer, your primary role will involve conducting original research on generative AI models. You will focus on exploring model architecture, training methodologies, fine-tuning techniques, and evaluation strategies. It is essential to maintain a strong publication record in esteemed conferences and journals, demonstrating your valuable contributions to the fields of Natural Language Processing (NLP), Deep Learning (DL), and Machine Learning (ML). In addition, you will be responsible for designing and experimenting with multimodal generative models that incorporate various data types such as text, images, and other modalities to enhance AI capabilities. Your expertise will be crucial in developing autonomous AI systems that exhibit agentic behavior, enabling them to make independent decisions and adapt to dynamic environments. Leading the design, development, and implementation of generative AI models and systems will be a key aspect of your role. This involves selecting suitable models, training them on extensive datasets, fine-tuning hyperparameters, and optimizing overall performance. It is imperative to have a deep understanding of the problem domain to ensure effective model development and implementation. Furthermore, you will be tasked with optimizing generative AI algorithms to enhance their efficiency, scalability, and computational performance. Techniques such as parallelization, distributed computing, and hardware acceleration will be utilized to maximize the capabilities of modern computing architectures. Managing large datasets through data preprocessing and feature engineering to extract critical information for generative AI models will also be a crucial aspect of your responsibilities. Your role will also involve evaluating the performance of generative AI models using relevant metrics and validation techniques. By conducting experiments, analyzing results, and iteratively refining models, you will work towards achieving desired performance benchmarks. Providing technical leadership and mentorship to junior team members, guiding their development in generative AI, will also be part of your responsibilities. Documenting research findings, model architectures, methodologies, and experimental results thoroughly is essential. You will prepare technical reports, presentations, and whitepapers to effectively communicate insights and findings to stakeholders. Additionally, staying updated on the latest advancements in generative AI by reading research papers, attending conferences, and engaging with relevant communities is crucial to foster a culture of learning and innovation within the team. Mandatory technical skills for this role include strong programming abilities in Python and familiarity with frameworks like PyTorch or TensorFlow. In-depth knowledge of Deep Learning concepts such as CNN, RNN, LSTM, Transformers LLMs (BERT, GEPT, etc.), and NLP algorithms is required. Experience with frameworks like Langgraph, CrewAI, or Autogen for developing, deploying, and evaluating AI agents is also essential. Preferred technical skills include expertise in cloud computing, particularly with Google/AWS/Azure Cloud Platform, and understanding Data Analytics Services offered by these platforms. Hands-on experience with ML platforms like GCP: Vertex AI, Azure: AI Foundry, or AWS SageMaker is desirable. Strong communication skills, the ability to work independently with minimal supervision, and a proactive approach to escalate when necessary are also key attributes for this role. If you have a Master's or PhD degree in Computer Science and 6 to 8 years of experience with a strong record of publications in top-tier conferences and journals, this role could be a great fit for you. Preference will be given to research scholars from esteemed institutions like IITs, NITs, and IIITs.,

Work Location: Bangalore (in-office) We're seeking hands-on Lead Software Engineers who can: Build production-ready AI solutions on AWS Guide distributed teams while continuously scouting and prototyping emerging AI technologies You'll join our Product Engineering group, owning end-to-end delivery of next-generation Amorphic AI solutions while mentoring engineers across global teams. What is Expected: Technical Leadership Lead the integration of cutting-edge AI/LLMs into Amorphic AI Solutions, ensuring seamless interoperability and optimal performance Design and architect complex software systems with focus on scalability, maintainability, and performance Architect production-grade RAG pipelines and multi-agent orchestration on AWS (Lambda, ECS/Fargate, Bedrock, SageMaker, DynamoDB, S3, EventBridge, Step Functions) Drive the design and implementation of scalable AI pipelines Development & Innovation Design, develop, test, and maintain scalable backend applications using Python and AWS services Stay current with AI advancements through hands-on experimentation with emerging frameworks (LangChain, Hugging Face Transformers, CrewAI) via prototypes and side projects Optimize AI solution performance focusing on cost-effectiveness, latency, and resource utilization Develop strategies for monitoring, maintaining, and improving deployed AI models in production Team Leadership Lead 5-10 engineers through design reviews, pair-programming, and PR feedback Conduct code reviews and design discussions to ensure adherence to best practices Collaborate with cross-functional teams globally to identify requirements and implement solutions Create and maintain comprehensive documentation for architecture, design decisions, and coding practices Preferred Candidate Profile BE / B.Tech in Computer Science or related field 8+ years of experience in software development Solid understanding of large language models (LLMs), including experience with prompt engineering, fine-tuning, or integrating LLM APIs (e.g., from OpenAI, Anthropic, or AWS Bedrock) Hands-on experience building AI solutions using latest tools and frameworks (e.g., langchain, crewAI), demonstrated through side projects, open-source contributions, or personal prototypes Proven leadership experience in managing and mentoring high-performing teams of software and application developers Exceptional proficiency in Python programming language Solid understanding of AWS ecosystem including Lambda functions, S3 buckets, EMR clusters, DynamoDB tables etc. Proven experience in a leadership role, leading software development teams in the delivery of complex projects Deep understanding of software architecture and design principles, with a focus on building scalable and maintainable systems Experience with distributed systems, microservices architecture, and cloud-based solutions Strong knowledge of software development best practices, including code reviews, testing, and CI/CD pipelines Experience working with AWS services and developing Cloud Native Applications using REST APIs is must have Experience working in an agile delivery environment, especially product engineering teams How We'll Take Care Of You: We believe in supporting our team members both professionally and personally. Here's a look at the comprehensive benefits and perks we offer: Financial Well-being & Security Competitive Compensation : Enjoy competitive salaries and bonuses that reward your hard work and dedication Robust Insurance Coverage : Benefit from health, life, and disability insurance to ensure you and your family are protected Provident Fund Eligibility : Secure your future with eligibility for the provident fund Work-Life Balance & Flexibility Flexible Working Hours : We offer flexible working hours to help you manage your personal and professional commitments Generous Paid Time Off : Take advantage of unlimited Paid Time Off (PTO), with a mandatory minimum of 1 week per year to ensure you recharge Comprehensive Leave Policies : We provide paid vacation days, sick leave, and holidays, plus supportive parental leave (maternity, paternity, and adoption) and bereavement leave when you need it most Professional Growth & Development Learning & Development : Elevate your skills with access to extensive certification and training programs Cutting-Edge Technologies : You'll work at the forefront of innovation with cutting-edge technologies, constantly igniting your passion for continuous learning and growth Culture & Community Recognition & Rewards : Your contributions won't go unnoticed with our recognition and reward programs Engaging Activities : Connect with your colleagues through company-sponsored events, outings, team-building activities, and retreats .

We are looking for a Technical Architect who has experience designing software solutions from the ground up, making high-level decisions about each stage of the process and leading a team of engineers to create the final product. To be successful as a Technical Architect, you should be an expert problem solver with a strong understanding of the broad range of software technologies and platforms available. Top candidates will also be excellent leaders and communicators. Responsibilities Collaborate with stakeholders (Product Owners, Engineers, Clients) to define and refine software architecture aligned with product vision. Design scalable, modular, and secure system architecture using microservices and modern design patterns. Create high-level product specifications, architecture diagrams, and technical documentation. Provide architectural blueprints, guidance, and technical leadership to development teams. Build and integrate AI-driven components, including Agentic AI (AutoGen, LangGraph), RAG pipelines, and LLM capabilities (Open-source and Commercial models). Define vector-based data pipelines and integrate vector databases such as FAISS, ChromaDB, or Azure AI Search. Lead the implementation of Prompt Engineering strategies to optimize LLM outcomes. Architect and deploy scalable, secure solutions on Azure Cloud, using services like Azure Kubernetes Service (AKS), Azure Functions, Azure Storage, and Azure DevOps. Ensure robust CI/CD and DevSecOps practices in place to streamline deployments and enforce compliance. Guide the team in troubleshooting, code reviews, performance tuning, and ensuring adherence to software engineering best practices. Conduct regular technical reviews, present progress updates, and ensure timely delivery of milestones. Drive innovation and exploration of emerging technologies, particularly in the field of Generative AI and Intelligent Automation. Requirements 10+ years of hands-on software development experience, with a strong Python background. 3+ years of experience in a Software or Solution Architect role. Proven experience in designing and building production-grade solutions using microservices architecture. Strong expertise in Agentic AI frameworks (AutoGen, LangGraph, CrewAI, LangChain, etc.). Working knowledge of LLMs (Open-source like LLaMA, Mistral; Commercial like OpenAI, Azure OpenAI). Solid experience with Prompt Engineering, RAG pipelines, and Vector Database integration. Experience deploying AI/ML solutions on Azure Cloud, leveraging PaaS components and cloud-native patterns. Proficiency with containerization and orchestration tools (Docker, Kubernetes). Knowledge of architectural patterns: event-driven, domain-driven design, CQRS, service mesh, etc. Familiarity with NLP tools, frameworks, and libraries (spaCy, Hugging Face, Transformers, etc.). Experience with Apache Airflow or other workflow orchestration tools. Strong communication and leadership skills to work cross-functionally with technical and non-technical teams.

58 years of experience in AI/ML or automation engineering. Strong hands-on experience with CrewAI or other LLM orchestration frameworks like LangChain, AutoGen, or Semantic Kernel. Proficiency in Python, including experience with async programming and API integration. Deep understanding of LLMs (OpenAI, Anthropic, Mistral, etc.) and prompt engineering. Familiarity with vector databases (e.g., Pinecone, FAISS, Chroma) and embeddings. Experience building and deploying production-ready agent-based solutions. Strong problem-solving skills and ability to translate business requirements into technical implementations.

As a candidate applying for this position, you should be prepared to attend face-to-face interviews and be open to the opportunity. The role offers a 5-day work week based in the office. Your responsibilities will include architecting and implementing REST APIs, designing and implementing high-performance applications with low latency, integrating GenAI-powered capabilities into backend systems, testing software for responsiveness and efficiency, collaborating with front-end developers, and troubleshooting application-related issues. You will also be expected to take initiatives in building efficient solutions for scalability and work closely with the infrastructure team in triaging major incidents. Additionally, you should have experience in analyzing and researching solutions, as well as developing and implementing recommendations accordingly. To qualify for this position, you should hold a Bachelor's Degree in Computer Science or a related field, along with a minimum of 4 years of professional experience. Expertise in JavaScript (ES6) and Node JS is essential, as well as a strong understanding of algorithms and data structures. Proficiency in frameworks like Express JS and Restify is required, along with experience in building backend services for handling large-scale data. You should be able to architect high-availability applications and servers on the cloud following best practices, with a preference for microservices architecture. Experience with MySQL, NoSQL databases like DynamoDB and MongoDB, as well as GenAI agentic frameworks is advantageous. Additionally, you should have experience with complex SQL queries, Node JS concepts, technical deep-dives into code, and building and deploying GenAI-powered backend services or tools. Understanding communication through WebSockets, clean architecture, SOLID principles, AWS, Docker containerization, Python, AI-assisted development tools, and Git is beneficial for this role. If you meet these requirements and are ready to take on these responsibilities, we welcome your application for this exciting opportunity.,

We are searching for a skilled and adaptable Data Engineer with proficiency in PySpark, Apache Spark, and Databricks, combined with knowledge in analytics, data modeling, and Generative AI/Agentic AI solutions. This position suits individuals who excel at the convergence of data engineering, AI systems, and business insights, contributing to impactful programs with clients. Your responsibilities will include designing, constructing, and enhancing distributed data pipelines utilizing PySpark, Apache Spark, and Databricks to cater to both analytics and AI workloads. You will also be tasked with supporting RAG pipelines, embedding generation, and data pre-processing for LLM applications. Additionally, creating and maintaining interactive dashboards and BI reports using tools like Power BI, Tableau, or Looker for business stakeholders and consultants will be part of your role. Furthermore, your duties will involve conducting adhoc data analysis to facilitate data-driven decision-making and rapid insight generation. You will be expected to develop and sustain robust data warehouse schemas, star/snowflake models, and provide support for data lake architecture. Integration with and support for LLM agent frameworks like LangChain, LlamaIndex, Haystack, or CrewAI for intelligent workflow automation will also fall under your purview. In addition, ensuring data pipeline monitoring, cost optimization, and scalability in cloud environments (Azure/AWS/GCP) will be important aspects of your work. Collaboration with cross-functional teams, including AI scientists, analysts, and business teams to drive use-case delivery, is key. Lastly, maintaining robust data governance, lineage, and metadata management practices using tools such as Azure Purview or DataHub will also be part of your responsibilities.,

Hi, Greetings from Sun Technology Integrators!! This is regarding a job opening with Sun Technology Integrators, Bangalore. Please find below the job description for your reference. Kindly let me know your interest and share your updated CV to nandinis@suntechnologies.com ASAP. Strong background in traditional AI/ML Experience building GenAI chatbots, agents, implementing tools with Gemini or similar vendors Fine tuning experience of LLMs Ability to work with LLM APIs Experience with modern Generative AI development frameworks and tools (LangChain, Vector DBs) Agentic Frameworks (e.g., LangGraph, CrewAI, ). Experience with prompt engineering Experience with RAG architecture Experience in Google Cloud and Vertex AI Experienced with Python Please let me know, if any of your friends are looking for a job change. Kindly share the references. Please Note: WFO- Work From Office (No hybrid or Work From Home) Shift Details: IST Shift - 12.30 PM to 9.30 PM IST -2 ways free cab facility(Pickup+Drop) Years of Exp-5 to 10 years Interview Mode- 2 rounds Virtual interview Thanks and Regards, Nandini S | Sr.Technical Recruiter Sun Technology Integrators Pvt. Ltd. nandinis@suntechnologies.com www.suntechnologies.com

Roles & Responsibilities GenAI Developer (5+ Years Experience) Minimum 5 years of overall experience , with at least 2 years of hands-on experience in building Generative AI (GenAI) solutions Strong working knowledge of Agentic AI frameworks , including experience in one or more of the following: LangGraph CrewAI Proven expertise in GenAI technologies , including: Python , LangChain , LangGraph , OpenAI APIs Azure Document Intelligence (ADI) Azure Service Bus Retrieval Augmented Generation (RAG) Experience in designing and implementing end-to-end GenAI applications with focus on scalability and enterprise-grade architecture Strong understanding of the Property & Casualty (P&C) Insurance domain and ability to apply GenAI solutions to relevant use cases Capable of integrating AI models with enterprise systems and APIs to build context-aware , intelligent applications Demonstrates clear communication skills , capable of working with technical and business stakeholders

5+ Years of experience in the design & development of state-of-the-art language models, Utilize off-the-shelf LLM services, such as Azure OpenAI, to integrate LLM capabilities into applications. Deep understanding of language models and a strong proficiency in designing and implementing RAG-based workflows to enhance content generation and information retrieval. Experience in building, customizing and fine-tuning LLMs via OpenAI studio extended through Azure OpenAI cognitive services for rapid PoCs Proven track record of successfully deploying and optimizing LLM models in cloud(AWS, Azure or GCP) for inference in production environments and proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. Apply prompt engineering techniques to design refined and contextually relevant prompts for language models. Monitor and analyse the performance of LLMs by experimenting with various prompts, evaluating results, and refining strategies accordingly. Building customizable, conversable AI agents for complex tasks using CrewAI and LangGraph to enhance Gen AI solutions Proficient in MCP(Model Context Protocol) for optimizing context-aware AI model performance and integration is a plus Basic Qualifications: Bachelors or Masters degree in computer science or a related discipline. Good communication & Interpersonal skills to interact with customers and partner teams Must be a quick learner & Self-starter who requires minimal supervision. Excellent Problem solving, Critical thinking & Analytics skills. Proficiency in english(Oral & Written)

We are looking for a GenAI/ML Engineer to design, develop, and deploy cutting-edge AI/ML models and Generative AI applications . This role involves working on large-scale enterprise use cases, implementing Large Language Models (LLMs) , building Agentic AI systems , and developing data ingestion pipelines . The ideal candidate should have hands-on experience with AI/ML development , Generative AI applications , and a strong foundation in deep learning , NLP , and MLOps practices. Key Responsibilities Design, develop , and deploy AI/ML models and Generative AI applications for various enterprise use cases. Implement and integrate Large Language Models (LLMs) using frameworks such as LangChain , LlamaIndex , and RAG pipelines . Develop Agentic AI systems capable of multi-step reasoning and autonomous decision-making . Create secure and scalable data ingestion pipelines for structured and unstructured data, enabling indexing, vector search, and advanced retrieval techniques. Collaborate with cross-functional teams (Data Engineers, Product Managers, Architects) to deploy AI solutions and enhance the AI stack. Build CI/CD pipelines for ML/GenAI workflows and support end-to-end MLOps practices. Leverage Azure and Databricks for training , serving , and monitoring AI models at scale. Required Qualifications & Skills (Mandatory) 4+ years of hands-on experience in AI/ML development , including Generative AI applications . Expertise in RAG , LLMs , and Agentic AI implementations. Strong experience with LangChain , LlamaIndex , or similar LLM orchestration frameworks. Proficiency in Python and key ML/DL libraries : TensorFlow , PyTorch , Scikit-learn . Solid foundation in Deep Learning , Natural Language Processing (NLP) , and Transformer-based architectures . Experience in building data ingestion , indexing , and retrieval pipelines for real-world enterprise use cases. Hands-on experience with Azure cloud services and Databricks . Proven track record in designing CI/CD pipelines and using MLOps tools like MLflow , DVC , or Kubeflow . Soft Skills Strong problem-solving and critical thinking ability. Excellent communication skills , with the ability to explain complex AI concepts to non-technical stakeholders. Ability to collaborate effectively in agile , cross-functional teams . A growth mindset , eager to explore and learn emerging technologies. Preferred Qualifications Familiarity with vector databases such as FAISS , Pinecone , or Weaviate . Experience with AutoGPT , CrewAI , or similar agent frameworks . Exposure to Azure OpenAI , Cognitive Search , or Databricks ML tools . Understanding of AI security , responsible AI , and model governance . Role Dimensions Design and implement innovative GenAI applications to address complex business problems. Work on large-scale, complex AI solutions in collaboration with cross-functional teams. Take ownership of the end-to-end AI pipeline , from model development to deployment and monitoring. Success Measures (KPIs) Successful deployment of AI and Generative AI applications . Optimization of data pipelines and model performance at scale. Contribution to the successful adoption of AI-driven solutions within enterprise use cases. Effective collaboration with cross-functional teams, ensuring smooth deployment of AI workflows. Competency Alignment AI/ML Development : Expertise in building and deploying scalable and efficient AI models. Generative AI : Strong hands-on experience in Generative AI , LLMs , and RAG frameworks. MLOps : Proficiency in designing and maintaining CI/CD pipelines and implementing MLOps practices . Cloud Platforms : Experience with Azure and Databricks for AI model training and serving.

Prompt Engineering and its strategies Should know how LLM works and its hyper parameter ( temperature, top_p) Agentic AI framework like langchain, lang graph, crew ai RAG LLM evaluation and observability Python Deployment on any one of cloud services

As a part of the global leader in Cloud, AI, and Digital technologies, you will be responsible for leveraging GenAI models and frameworks to enhance the efficiency and productivity of businesses worldwide. Your role will involve serving as the primary technical expert for GenAI technologies, focusing on developing, implementing, and optimizing advanced AI models and solutions to expand our GenAI footprint across clients. You will provide technical leadership, drive innovation, and ensure the successful integration of AI technologies into our IT services for clients. Your responsibilities will include defining best practices, standards, and templates for AI solutions, conducting workshops, demos, and client presentations on GenAI use cases, and collaborating closely with cross-functional teams to identify, evaluate, and implement use cases across different customers. In addition, you will evaluate and integrate emerging GenAI technologies to enhance conversational AI capabilities, provide technical leadership, mentorship, and guidance to teams, troubleshoot and resolve complex platform integration and functionality issues. You will also be hands-on in independently building quick prototypes and demonstrating them to key decision-makers. To be successful in this role, you should have 10+ years of total IT experience with at least 3-4 years of hands-on experience with AI/GenAI technologies. Expertise in NLP, NLU, NLQ, and NLG technologies is essential, along with Core Python proficiency to build applications and engineer GenAI solutions at an enterprise scale. You must have delivered production-grade projects on agentic AI frameworks, as well as hands-on experience with agentic AI frameworks such as Autogen, Langraph, or Crew.AI. Experience with NLQ to SQL-based GenAI applications using core Python tools and frameworks, databases, data warehouses, and data lakes on cloud platforms is required. Deep knowledge of architecting product-scale GenAI applications on Microsoft Azure Cloud, AWS Cloud, or GCP cloud environments is a must. Strong programming skills in Python, Node.js, Java, or similar, API programming, familiarity with LLMs, prompt engineering, fine-tuning, and embeddings are desired. Excellent problem-solving skills, solution architecture capabilities, and client-facing communication skills are essential. The ability to translate business needs into technical solutions, manage multiple projects and priorities in a fast-paced environment, and work with cloud platforms is crucial. Moreover, expertise in building technical proposals with winning engineering architectures and technical articulation for CXO level audience, and experience in developing fast PoVs and blueprints on new and emerging GenAI models, tools, frameworks, and other stack will be advantageous for this role.,

At InnovationM , we're shaping the future of enterprise AI and are looking for a Senior Agentic AI Engineer to lead the design and development of cutting-edge agentic frameworks. Youll help build a scalable AI foundation that empowers multiple teams to deploy intelligent agents with autonomy, memory, and reasoning capabilities. Key Skills: Python | LangGraph | CrewAI | RAG | LLMs | Agentic Frameworks Tool Integration | Vector Databases | Autonomous Decision-Making Human-in-the-Loop | Secure, Scalable Architectures What Youll Do: Architect enterprise-grade AI frameworks Build reusable agentic patterns using LangGraph, CrewAI, AutoGPT Enable tools like APIs, vector stores, RPA, and internal services Collaborate across teams to bring autonomy into complex workflows Mentor and guide teams on the future of agentic AI Why Join Us? Work on the latest in AI/ML and agentic systems Engage with large-scale clients and impactful projects Thrive in a culture of innovation, learning & development Location: Noida Sec-126 l 5 Days work from Office Apply now: nikita.gautam@innovationm.com

Job Title: Software Engineer Job Type: Full-Time Experience Level: Mid-Level (4 - 6 years) What You Can Expect from the Job As a Mid-Level AI Engineer focused on Large Language Model (LLM) development , you will: Build and optimize LLM-powered applications using LangChain , CrewAI , and other orchestration tools. Implement context management protocols to improve model memory and performance. Design and deploy user-friendly interfaces using OpenWebUI for interacting with LLMs. Prepare and manage datasets for training, fine-tuning, and inference. Integrate vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG) pipelines. Collaborate with cross-functional teams on prompt engineering, agent workflows, and intelligent automation. Stay current with the latest developments in LLMs, open-source tools, and AI research. Contribute to scalable, ethical, and production-ready AI systems. What Will Help You Do the Job Well Must have skills/characteristics 46 years of experience in AI/ML engineering, with a focus on NLP or LLMs. Strong proficiency in Python and experience with frameworks like LangChain , CrewAI , and Transformers (Hugging Face) . Hands-on experience with OpenWebUI for deploying and managing LLM interfaces. Solid understanding of model context protocols , token limits, and memory handling. Experience in data preparation , including cleaning, labelling, and formatting for LLM workflows. Familiarity with vector databases , embedding models , and retrieval systems . A collaborative mindset and the ability to work in fast-paced, agile environments. Other desirable skills/characteristics Experience with agent-based architectures and multi-agent coordination. Knowledge of LLMOps , model deployment, and monitoring tools. Familiarity with Microsoft Co-pilot and its integration into enterprise workflows. Contributions to open-source AI projects or research publications. Knowledge if ISMS Principles and best practices. Willingness to Travel domestic/international. Thank you for your interest with CCS. We hope you find a meaningful career! Please send your profiles to careers@ccs-technologies.com We will Trust, Recognize, Care You will – Learn, Contribute, Grow

As an AI Research Scientist, your role will involve developing the overarching technical vision for AI systems that cater to both current and future business needs. You will be responsible for architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Working in partnership with product management, you will design agile project roadmaps that align technical strategy with market needs. Additionally, you will coordinate with data engineering teams to guarantee smooth data flows, quality, and governance across various data sources. Your responsibilities will also include leading the design of reference architectures, roadmaps, and best practices for AI applications. You will evaluate emerging technologies and methodologies, recommending innovations that can be integrated into the organizational strategy. Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems will be crucial aspects of your role. Leveraging containerization (Docker, Kubernetes) and cloud services, you will streamline the deployment and scaling of AI systems. Implementing robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will also be part of your duties. Project management will be a key component of your role, overseeing the planning, execution, and delivery of AI and ML applications within budget and timeline constraints. You will be responsible for the entire lifecycle of AI application development, from conceptualization and design to development, testing, deployment, and post-production optimization. Enforcing security best practices throughout each phase of development, with a focus on data privacy, user security, and risk mitigation, will be essential. Furthermore, providing mentorship to engineering teams and fostering a culture of continuous learning will play a significant role in your responsibilities. In terms of mandatory technical and functional skills, you should possess a strong background in working with or developing agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with robust knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras, is required. You should also have proven experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) for building and deploying scalable AI solutions. Hands-on skills with containerization (Docker), orchestration frameworks (Kubernetes), and related DevOps tools like Jenkins and GitLab CI/CD are necessary. Experience using Infrastructure as Code (IaC) tools such as Terraform or CloudFormation to automate cloud deployments is essential. Additionally, proficiency in SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and expertise in designing distributed systems, RESTful APIs, GraphQL integrations, and microservices architecture are vital for this role. Knowledge of event-driven architectures and message brokers (e.g., RabbitMQ, Apache Kafka) is also required to support robust inter-system communications. Preferred technical and functional skills include experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack) to ensure system reliability and operational performance. Familiarity with cutting-edge libraries such as Hugging Face Transformers, OpenAI's API integrations, and other domain-specific tools is advantageous. Experience in large-scale deployment of ML projects, along with a good understanding of DevOps/MLOps/LLM Ops and training and fine-tuning of Large Language Models (SLMs) like PALM2, GPT4, LLAMA, etc., is beneficial. Key behavioral attributes for this role include the ability to mentor junior developers, take ownership of project deliverables, contribute to risk mitigation, and understand business objectives and functions to support data needs. If you have a Bachelor's or Master's degree in Computer Science, certifications in cloud technologies (AWS, Azure, GCP), and TOGAF certification (good to have), along with 11 to 14 years of relevant work experience, this role might be the perfect fit for you.,

You will be responsible for building curated enterprise-grade solutions for GenAI application deployment at a production scale for clients. This role demands a solid understanding and hands-on skills in GenAI application deployment, encompassing development and engineering skills. You will need to possess expertise in data ingestion, selecting the appropriate LLMs, implementing simple and advanced RAG, guardrails, prompt engineering for optimization, traceability, security, LLM evaluation, observability, and deployment at scale on cloud or on-premise. It is essential for candidates to demonstrate knowledge of agentic AI frameworks due to the rapid evolution of this space. Strong background in ML with engineering skills is highly preferred for the LLMOps role. You should have 3 - 5 years of experience working on ML projects, involving business requirement gathering, model development, training, deployment at scale, and monitoring model performance for production use cases. Proficiency in Python, NLP, Data Engineering, Langchain, Langtrace, Langfuse, RAGAS, AgentOps (optional) is crucial. Experience with proprietary and open-source large language models, LLM fine-tuning, creating distilled models from hosted LLMs, and building data pipelines for model training is required. You should also have experience in model performance tuning, RAG, guardrails, prompt engineering, evaluation, and observability. Prior experience in GenAI application deployment on cloud and on-premises at scale for production, creating CI/CD pipelines, working with Kubernetes, and deploying AI services on at least one cloud platform such as AWS, GCP, or Azure is necessary. Proficiency in creating workable prototypes using Agentic AI frameworks like CrewAI, Taskweaver, AutoGen, and light-weight UI development using streamlit or chainlit (optional) is beneficial. Desired experience with open-source tools for ML development, deployment, observability, and integration is an added advantage. A background in DevOps and MLOps will be a plus. You should be familiar with collaborative code versioning tools like GitHub/GitLab and possess excellent communication and presentation skills. A degree in Computer Science, related technical field, or equivalent is required. If you are someone who thrives in a dynamic environment and enjoys collaborating with enthusiastic individuals, this opportunity is perfect for you.,

You will be responsible for leveraging GenAI models and frameworks to build applications and optimize AI solutions for clients. As the primary technical expert in GenAI technologies, you will focus on enhancing the GenAI footprint by developing and implementing advanced AI models. Your role will involve defining best practices, conducting workshops and demos, collaborating with cross-functional teams, and integrating emerging GenAI technologies for improving conversational AI capabilities. Additionally, you will provide technical leadership, mentorship, and guidance to teams, troubleshoot platform integration issues, and independently build prototypes to demonstrate to key decision-makers. To excel in this position, you should have at least 10 years of IT experience, with 3-4 years specifically in AI/Gen AI technologies such as OpenAI, Anthropic, or Hugging Face. Proficiency in NLP, NLU, NLQ, NLG technologies, and core Python expertise for building enterprise-scale applications are essential. You must have delivered production-grade projects on agentic AI frameworks, hands-on experience with frameworks like Autogen, Langraph, or Crew.AI, and expertise in NLQ to SQL-based GenAI applications using Python tools. Experience with cloud platforms like Microsoft Azure, AWS, or GCP, API integrations, and programming skills in Python, Node.js, or Java are also required. Moreover, you should possess strong problem-solving skills, solution architecture capabilities, and client-facing communication abilities to translate business requirements into technical solutions effectively. The ability to manage multiple projects in a fast-paced environment and experience working with cloud platforms will be beneficial. Additionally, expertise in building technical proposals, fast PoVs, and blueprints on new GenAI models and tools are desired for this role.,

We are looking for a skilled, motivated, and quick-learning Full Stack Developer to join our team dedicated to cutting-edge Gen AI development work. As a Full Stack Developer, you will be responsible for creating innovative applications and solutions that encompass both frontend and backend technologies. While our solutions often involve the use of Retrieval Augmented Generation (RAG) and Agentic frameworks, your role will extend beyond these technologies to encompass a variety of AI tools and techniques. Your responsibilities will include developing and maintaining web applications using Angular, NDBX frameworks, and other modern technologies. You will design and implement databases in Postgres DB, employ ingestion and retrieval pipelines utilizing pgvector and neo4j, and ensure the implementation of efficient and secure data practices. Additionally, you will work with various generative AI models and frameworks such as LangChain, Haystack, and LlamIndex for tasks like chucking, embeddings, chat completions, and integration with different data sources. You will collaborate with team members to integrate GenAI capabilities into applications, write clean and efficient code adhering to company standards, conduct testing to identify and fix bugs, and utilize collaboration tools like GitHub for effective team working and code management. Staying updated with emerging technologies and applying them to operations will be essential, showcasing a strong desire for continuous learning. Qualifications and Experience: - Bachelor's degree in Computer Science, Information Technology, or a related field with at least 6 years of working experience. - Proven experience as a Full Stack Developer with a focus on designing, developing, and deploying end-to-end applications. - Knowledge of front-end languages and libraries such as HTML/CSS, JavaScript, XML, and jQuery. - Experience with Angular and NDBX frameworks, as well as database technologies like Postgres DB and vector databases. - Proficiency in developing APIs following OpenAPI standards. - Familiarity with generative AI models on cloud platforms like Azure and AWS, including techniques like Retrieval Augmented Generation, Prompt engineering, Agentic RAG, and Model context protocols. - Experience with collaboration tools like GitHub and docker images for packaging applications. At Allianz, we believe in fostering a diverse and inclusive workforce. We are proud to be an equal opportunity employer that values bringing your authentic self to work, regardless of background, appearance, preferences, or beliefs. Together, we can create an environment where everyone feels empowered to explore, grow, and contribute to a better future for our customers and the global community. Join us at Allianz and let's work together to care for tomorrow.,

Job Position Title: Senior Associate_ APA Developer_Agentic Automation_Advisory_Bangalore Responsibilities: Design and develop agentic automation workflows using frameworks such as LangGraph, AutoGen, CrewAI, and other multi-agent systems (e.g., MCP, A2A) to automate complex business processes. Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enhanced contextual understanding and accurate response generation in automation tasks. Integrate open-source LLMs (e.g. LLaMA) and closed-source LLMs (e.g., OpenAI, Gemini, Vertex AI) to power agentic systems and generative AI applications. Develop robust Python-based solutions using libraries like LangChain, Transformers, Pandas, and PyTorch for automation and AI model development. Implement and manage CI/CD pipelines, Git workflows, and software development best practices to ensure seamless deployment of automation solutions. Work with structured and unstructured data, applying prompt engineering and fine-tuning techniques to enhance LLM performance for specific use cases. Query and manage databases (e.g., SQL, NoSQL) for data extraction, transformation, and integration into automation workflows. Collaborate with stakeholders to translate technical solutions into business value, delivering clear presentations and documentation. Stay updated on advancements in agentic automation, generative AI, and LLM technologies to drive innovation and maintain competitive edge. Ensure scalability, security, and performance of deployed automation solutions in production environments. Experience: 4+ years of hands-on experience in AI/ML, generative AI, or automation development. Proven expertise in agentic frameworks like LangGraph, AutoGen, CrewAI, and multi-agent systems. Experience building and deploying RAG-based solutions for automation or knowledge-intensive applications. Hands-on experience with open-source LLMs (Hugging Face) and closed-source LLMs (OpenAI, Gemini, Vertex AI). Technical Skills: Advanced proficiency in Python and relevant libraries (LangChain, Transformers, Pandas, PyTorch, Scikit-learn). Strong SQL skills for querying and managing databases (e.g., PostgreSQL, MongoDB). Familiarity with CI/CD tools (e.g., Jenkins, GitHub Actions), Git workflows, and containerization (e.g., Docker, Kubernetes). Experience with Linux (Ubuntu) and cloud platforms (AWS, Azure, Google Cloud) for deploying automation solutions. Knowledge of automation tools (e.g., UiPath, Automation Anywhere) and workflow orchestration platforms. Soft Skills: Exceptional communication skills to articulate technical concepts to non-technical stakeholders. Strong problem-solving and analytical skills to address complex automation challenges. Ability to work collaboratively in a fast-paced, client-facing environment. Proactive mindset with a passion for adopting emerging technologies. Preferred Qualifications Experience with multi-agent coordination protocols (MCP) and agent-to-agent (A2A) communication systems. Familiarity with advanced generative AI techniques, such as prompt chaining, tool-augmented LLMs, and model distillation. Exposure to enterprise-grade automation platforms or intelligent process automation (IPA) solutions. Contributions to open-source AI/automation projects or publications in relevant domains. Certification in AI, cloud platforms, or automation technologies (e.g., AWS Certified AI Practitioner, RPA Developer). Mandatory skill sets: Agentic, LLM, RAG, AIML, LangGchain Preferred skill sets: Agentic, LLM, RAG, AIML, LangGchain, Gen AI Years of experience required: 4-7 Years

As an AI Azure Architect, your primary responsibility will be to develop the technical vision for AI systems that cater to the existing and future business requirements. This involves architecting end-to-end AI applications, ensuring seamless integration with legacy systems, enterprise data platforms, and microservices. Collaborating closely with business analysts and domain experts, you will translate business objectives into technical requirements and AI-driven solutions. Additionally, you will partner with product management to design agile project roadmaps aligning technical strategies with market needs. Coordinating with data engineering teams is essential to ensure smooth data flows, quality, and governance across different data sources. Your role will also involve leading the design of reference architectures, roadmaps, and best practices for AI applications. Evaluating emerging technologies and methodologies to recommend suitable innovations for integration into the organizational strategy is a crucial aspect of your responsibilities. You will be required to identify and define system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems. Leveraging containerization (Docker, Kubernetes) and cloud services will streamline the deployment and scaling of AI systems. Implementation of robust versioning, rollback, and monitoring mechanisms to ensure system stability, reliability, and performance will be part of your duties. Moreover, you will oversee the planning, execution, and delivery of AI and ML applications, ensuring they are completed within budget and timeline constraints. Managing project goals, allocating resources, and mitigating risks will fall under your project management responsibilities. You will be responsible for overseeing the complete lifecycle of AI application developmentfrom conceptualization and design to development, testing, deployment, and post-production optimization. Emphasizing security best practices during each development phase, focusing on data privacy, user security, and risk mitigation, is crucial. In addition to technical skills, the ideal candidate for this role should possess key behavioral attributes such as the ability to mentor junior developers, take ownership of project deliverables, and contribute towards risk mitigation. Understanding business objectives and functions to support data needs is also essential. Mandatory technical skills for this position include a strong background in working with agents using langgraph, autogen, and CrewAI. Proficiency in Python, along with knowledge of machine learning libraries like TensorFlow, PyTorch, and Keras, is required. Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform), containerization tools (Docker), orchestration frameworks (Kubernetes), and DevOps tools (Jenkins, GitLab CI/CD) is essential. Proficiency in SQL and NoSQL databases, designing distributed systems, RESTful APIs, GraphQL integrations, and event-driven architectures are also necessary. Preferred technical skills include experience with monitoring and logging tools, cutting-edge libraries like Hugging Face Transformers, and large-scale deployment of ML projects. Training and fine-tuning of Large Language Models (LLMs) is an added advantage. Educational qualifications for this role include a Bachelor's/Master's degree in Computer Science, along with certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification. The ideal candidate should have 11 to 14 years of relevant work experience in this field.,