71 Crewai Jobs - Page 3

Responsibilities: * Develop AI/ML models using Python, Agentic AI, CrewAI, Generative AI tools. * Collaborate with cross-functional teams on project delivery. * Optimize model performance through data analysis and iteration. Flexi working Provident fund

Should have exp with Agen c frameworks like Crew AI, Lang, graph, Swarm AI etc. Must have contributed significantly to the development of at least 2 Gen AI projects. Must have worked with mul ple Gen AI models including GPT, Claude, Qwen, Lama etc.

Project description We're seeking a strong and creative Software Engineer eager to solve challenging problems of scale and work on cutting edge technologies. In this project, you will have the opportunity to write code that will impact thousands of users every month. You'll implement your critical thinking and technical skills to develop cutting edge software, and you'll have the opportunity to interact with teams across disciplines. In Luxoft, our culture is one that strives on solving difficult problems focusing on product engineering based on hypothesis testing to empower people to come up with ideas. In this new adventure, you will have the opportunity to collaborate with a world-class team in the field of Insurance by building a holistic solution, interacting with multidisciplinary teams. Responsibilities Build scripts that can handle parallel and batch processing and ensure execution with best performance parameters. Fine Tune existing scripts for performance Manage the end-to-end development using Python Should be able to bring best standards and practices in python coding from previous experience. Skills Must have Minimum 6+ years of relevant professional experience on core Python development and CrewAI(open source multiagent orchestration framework) mandatory Automate multiagent workflows using CrewAI Should be hands-on at scripting, programming especially in Python Should be capable of designing the program independently e.g. Python wrappers around other programs / scripts Should have been working on Agile DevOps culture [ADO ] Kanban and sprints. Should be senior enough for matured interactions internally and with Clients Nice to have Knowledge of Open Telemetry , SDK, APIs and client server models Acquaintance with IBM Z mainframe systems and relevant components like Omnibus, MQ, CICS, DB2, IMS Exposure to Monitoring cum observability domain Other Languages English: C2 Proficient Location - Pune,Bangalore,Hyderabad,Chennai,Noida

What you'll do Greetings from Data Security Council of India...!! The Data Security Council of India (DSCI) is a not-for-profit, industry body for data protection in India, setup by nasscom committed to making cyberspace safe, secure, and trustworthy by establishing cybersecurity best practices, standards, and initiatives in cyber security and privacy. DSCI engages with governments, regulators, industry sectors, and think tanks on policy advocacy, thought leadership, capacity building, and outreach initiatives. For more information, visit: www.dsci.in. We are seeking a dynamic and technically proficient AI/ML Engineer to support our AI/ML R&D initiatives in cybersecurity and take ownership of TechSagar.in a knowledge repository for India's emerging technology capabilities. The ideal candidate will possess hands-on experience in generative AI, emerging technologies, and product management. This is a hybrid role combining deep technical development with stakeholder engagement and platform evangelism. Role & responsibilities : AI/ML & Cybersecurity Innovation Support R&D efforts to prototype generative AI models for real-time threat detection and cybersecurity. Design, develop, and deploy machine learning models tailored to cyber threat intelligence and anomaly detection. Research and implement novel AI approaches, including multi-agent and reasoning-based systems. Develop distributed security monitoring frameworks using tools like AutoGen , CrewAI , etc. Build LLM-powered threat analysis tools using LangChain , LlamaIndex , and integrate with enterprise infrastructure. Apply MLOps best practices for model deployment, performance monitoring, and continuous integration. Optimize vector stores (Qdrant, FAISS, Pinecone, etc.) for RAG-based systems. Create synthetic datasets for AI training and model evaluation. Use Pydantic for data validation within AI pipelines. TechSagar Product Responsibilities Manage and evolve the TechSagar.in platformenhancing features, ensuring data integrity, and driving usage. Liaise with tech partners, government bodies, startups, and academia to enrich platform content. Strategize and execute industry engagement plans to market TechSagar and establish its relevance. Represent TechSagar in external forums, conferences, and industry meetings. Collect user feedback, define product roadmap, and ensure alignment with AI/ML advancements. Required Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, or related field. 12 years of hands-on experience in AI/ML model development and deployment. Strong programming expertise in Python . Familiarity with LangChain , LlamaIndex , and large language models (LLMs). Experience in applying AI to cybersecurity or vulnerability analysis. Good understanding of machine learning algorithms, data pipelines, and model evaluation. Excellent communication skills for technical and stakeholder engagement Preferred Skills: Exposure to generative AI , LLMs, and chain-of-thought reasoning techniques. Working knowledge of MLOps tools such as MLflow , Docker , etc. Familiarity with FastAPI or Flask for API development. Ability to preprocess, clean, and analyze large datasets efficiently. Experience in integrating AI tools with legacy or existing security systems. Technologies & Frameworks: LLM Frameworks: LangChain, LlamaIndex Multi-agent Systems: AutoGen, CrewAI Vector Databases: FAISS, Pinecone, Qdrant, Elasticsearch, AstraDB MLOps Tools: MLflow, Docker Programming & APIs: Python, FastAPI/Flask Data Validation: Pydantic Why Join Us? Be at the forefront of AI innovation in cybersecurity and national technology initiatives. Lead and shape a strategic tech product (TechSagar) with national impact. Collaborate with thought leaders in the AI, cybersecurity, and emerging tech ecosystem.

Were seeking a forward-thinking Gen AI Engineer to design, implement, and optimize cutting-edge agentic AI solutions using frameworks such as Crew.ai , LangChain , and LangGraph . You will work at the intersection of LLMs , Retrieval-Augmented Generation (RAG) systems, and NLP , enabling impactful AI applications across diverse domains. Key Responsibilities Design and deploy autonomous AI agents and multi-agent systems using LLMs such as GPT-4o, Claude, and LLaMA, leveraging Crew.ai, LangChain (and LangGraph). Own the AI solution lifecycle , including data acquisition, model experimentation, fine-tuning, deployment, and production monitoring. Develop scalable AI backends and pipelines using Python with frameworks like PyTorch or TensorFlow, deploying via REST APIs (FastAPI) on cloud platforms like AWS or Azure. Implement RAG-based systems by integrating open-source LLMs (via Hugging Face or Ollama) with vector databases (e.g., Pinecone, ChromaDB) and structured data stores (SQL/NoSQL). Collaborate with cross-functional teams to ensure reliable, maintainable, and impactful AI solutions. Required Skills & Experience 2 to 5 years of experience in AI/ML, NLP, Generative AI, with a focus on agentic AI systems . Strong proficiency in Python and hands-on experience building RAG systems and deploying open-source LLMs. Experience developing AI-driven backends and services with a strong understanding of scalability and performance. Familiarity with vector search technologies, database integration, and cloud-native architectures. Excellent communication and collaboration skills; ability to work effectively in a team environment. Education B.Tech/B.E. or M.Tech/M.E. in Computer Science, AI/ML, or a related field. Role: Gen AI Engineer Designation: AI Developer Experience: 2-5 Years (AI/ML, NLP, Generative AI): Location: Pune

Key Responsibilities: Agentic AI solution implementation leveraging Azure ecosystem, open-source RPA tools and scripting solutions where needed. Automation Solution Development : Create, deploy, and optimize automation workflows and BOTs using Agentic AI frameworks like Autogen. Leverage AI-driven processes to enable smart automation in business operations. Hands-on Cloud Integration : Design and implement automation solutions that integrate seamlessly with Microsoft Azure services (such as Azure Functions , Logic Apps , Azure Storage ) and other cloud-based tools to improve scalability and performance. AI and Python Libraries : Utilize Agentic AI frameworks for enhancing automation processes, and use Python libraries like Playwright for web automation, browser interaction, and testing. Implement machine learning models or AI algorithms where applicable to automate decision-making and data processing tasks. Scripting & Customization : Develop custom scripts in languages such as Python , PowerShell , JavaScript , and others to extend the functionality of RPA solutions, optimize workflows, and troubleshoot complex scenarios. Stakeholder Engagement : Collaborate with business analysts, IT teams, and key stakeholders to gather requirements, align automation goals with business priorities, and ensure automation solutions meet the desired business outcomes. Process Optimization : Continuously monitor, analyze, and optimize existing automation systems to enhance performance, reduce processing times, and ensure robustness. Identify opportunities to further automate manual processes across departments. Technical Leadership & Mentorship : Provide leadership, mentorship, and training to Agentic AI developers and junior engineers. Share best practices and foster a collaborative environment to ensure high standards of automation development.

We are seeking a skilled and innovative AI Agent Developer to design, build, and maintain autonomous AI agents capable of performing complex tasks using large language models (LLMs), APIs, and structured environments. The ideal candidate will have a strong foundation in software engineering, experience with AI frameworks, and a passion for building intelligent, adaptive systems. Immediate joiners will be preferred. Key Responsibilities: • Design, develop, and deploy AI agents capable of autonomous decision-making and task execution. • Integrate agents with LLMs (e.g., OpenAI GPT, Claude, Mistral) and external APIs for dynamic reasoning and action. • Implement memory, planning, and tool-use capabilities in agent architectures. • Collaborate with data scientists and backend engineers to optimize performance and scalability. • Monitor and evaluate agent behavior, adapting systems based on real-world feedback. • Contribute to research and innovation on agent frameworks and human-AI interaction models. Required Skills & Qualifications: • Bachelors or Masters degree in Computer Science, Artificial Intelligence, or related field. • 5+ years of experience with Python, AI/ML frameworks (LangChain, AutoGen, etc.), or agent-based modeling. • Experience with RESTful APIs, cloud platforms (AWS, Azure, GCP), and vector databases (e.g., Pinecone, Weaviate). • Understanding of reinforcement learning, planning algorithms, and prompt engineering. • Excellent problem-solving and communication skills. Preferred Qualifications: • Experience building agents in environments like ReAct, AutoGPT, BabyAGI, or custom frameworks. • Background in cognitive architectures, multi-agent systems, or human-in-the-loop systems. • Exposure to ethical considerations and safety in autonomous AI systems. Interested candidates share resume at meenakshi.middha@alcortech.com with CCTC,ECTC and notice period details.

Role & responsibilities We are seeking an exceptional Data Scientist with specialized expertise in developing multi-agent AI systems. In this role, you will design, implement, and optimize complex AI ecosystems where multiple intelligent agents collaborate to solve sophisticated problems. You will leverage your deep understanding of generative AI, retrieval-augmented generation (RAG), and prompt engineering to create cutting-edge solutions that push the boundaries of artificial intelligence. Key Responsibilities Design and develop generative AI-based multi-agent systems that can collaborate, communicate, and coordinate to achieve complex objectives Architect and implement RAG-based chatbot solutions that effectively leverage knowledge bases and external data sources Create sophisticated prompt engineering strategies to optimize AI agent behavior and inter-agent communication Build, train, and fine-tune generative AI models for various applications within multi-agent systems Develop robust evaluation frameworks to measure and improve multi-agent system performance Implement efficient knowledge sharing mechanisms between AI agents Write clean, efficient, and well-documented Python code for production-ready AI systems Collaborate with cross-functional teams to integrate multi-agent systems into broader product ecosystems Stay at the forefront of AI research and incorporate state-of-the-art techniques into our solutions Preferred candidate profile Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field 4+ years of professional experience in data science or machine learning engineering Extensive experience with Python programming and related data science/ML libraries Demonstrated expertise in developing and deploying generative AI models (e.g., LLMs, diffusion models) Proven experience building RAG-based systems and implementing vector databases Strong background in prompt engineering for large language models Experience designing and implementing generative AI-based multi-agent architectures Excellent problem-solving skills and ability to optimize complex AI systems Preferred Qualifications Experience with LangChain, AutoGPT, CrewAI, or similar frameworks for building agent-based systems Familiarity with orchestration tools for managing complex AI workflows Knowledge of agent communication protocols and collaborative problem-solving frameworks Experience with distributed systems and cloud computing platforms (AWS, GCP, Azure) Contributions to open-source AI projects or research publications in relevant fields Experience with knowledge graphs and semantic reasoning systems Familiarity with MLOps practices and deployment of AI systems at scale

We are seeking a highly skilled and motivated Senior Data Scientist with 56 years of experience to drive the development of intelligent AI systems. This role requires extensive hands-on experience with Large Language Models (LLMs) , strong background in Agentic AI , Machine Learning , and Python programming . You will work on designing autonomous agents, building scalable ML pipelines, and integrating advanced LLM-powered solutions into real-world products. Key Responsibilities: Architect and implement agentic AI systems that use LLMs for autonomous reasoning, planning, and multi-step task execution. Lead the development, fine-tuning, evaluation, and deployment of Large Language Models (LLMs) using frameworks like Hugging Face Transformers, LangChain, LLM orchestration tools, and vector databases. Develop ML models using supervised, unsupervised, and reinforcement learning techniques, and integrate them into production environments. Design and build end-to-end machine learning pipelines, including data ingestion, feature engineering, training, and deployment. Optimize model performance and latency in real-world applications and implement model monitoring and retraining strategies. Collaborate with cross-functional teams including product, engineering, and business to translate AI capabilities into product features. Mentor junior data scientists and contribute to the team's technical excellence and innovation. Required Skills & Experience: 56 years of professional and relevant experience in data science, AI, or machine learning roles. Proven hands-on experience with LLMs, including fine-tuning, prompt engineering, and RAG (Retrieval-Augmented Generation) pipelines. Deep expertise in Python and ML libraries such as scikit-learn, PyTorch, TensorFlow, and transformers. Strong understanding of agentic AI principles, autonomous agents, and task orchestration. Experience with cloud platforms (AWS, GCP, or Azure) and scalable infrastructure for deploying AI models. Exposure to API development, ML model serving, and integration with real-time systems. Excellent communication and collaboration skills in cross-functional environments. Educational Qualification: Bachelor of Technology (B.Tech) in Computer Science, Data Science, Artificial Intelligence, or a related field from a recognized institution. Preferred Qualifications: Contributions to open-source AI/ML projects or research publications related to LLMs or agent-based systems. Familiarity with LangChain, AutoGPT, CrewAI, or other agent orchestration frameworks. Experience with vector databases (e.g., FAISS, Pinecone) and knowledge of semantic search. Understanding of multi-agent collaboration, goal decomposition, and planning architectures.

Key Responsibilities: Design and development of AI-driven applications using frameworks such as LangChain, LangGraph, CrewAI, AutoGPT, and Autogen. Build and maintain RESTful APIs, GraphQL endpoints, and gRPC services to support scalable AI features. Support the development of intelligent agents and multi-agent collaboration mechanisms. Implement reasoning techniques including ReAct, Chain-of-Thought (CoT), and Tree-of-Thought (ToT) as part of AI workflows. Contribute to retrieval-augmented generation (RAG) pipelines using vector stores like Weaviate, Pinecone, FAISS, or ChromaDB. Integrate tool-use APIs, function calling, MCP, and external workflows via tools like Zapier or N8N. Work with orchestration tools such as Airflow, Ray, or Temporal to manage agent workflows and data pipelines. Collaborate with AI/ML engineers, product managers, and other developers in building intelligent, production-grade applications. Required Qualifications: 3-5 years of backend or full-stack development experience, with working on Generative or Agentic AI solutions. Proficiency in Python (preferred), with working knowledge of TypeScript/Node.js, Go, or Java. Hands-on experience developing REST APIs, GraphQL endpoints, and/or gRPC-based services. Familiarity with integrating LLMs like GPT-4, Claude, Gemini, Mistral, or LLaMA. Exposure to frameworks such as LangChain, LlamaIndex, or CrewAI. Basic understanding of vector databases and semantic search tools (e.g., FAISS, Pinecone). Experience working in cloud environments (AWS, GCP, Azure) and with containerization tools (Docker, Kubernetes).

Responsibilities Job Responsibilities: Architect and Design scalable and efficient AI solutions, leveraging technologies such as LangChain, Agentic AI, RAG, Event driven architecture using Kafka etc. Collaborate with cross-functional teams to identify business needs and develop tailored solutions Provide technical leadership and guidance to junior team members Stay up-to-date with the latest advancements in AI, machine learning, and data science, and apply this knowledge to improve our solutions Communicate complex technical concepts to non-technical stakeholders and team members Troubleshoot and resolve technical issues, and provide support to ensure high system uptime and performance Develop and maintain technical documentation, and ensure that all solutions are well-documented and easily maintainable Technical and Professional Requirements: Preferred Qualifications: Experience with Agentic Frameworks such LangGraph, AutoGen, CrewAI Experience with cloud-based technologies, such as AWS or Azure Familiarity with containerization using Docker, and orchestration using Kubernetes Familiarity with agile development methodologies, such as Scrum or Kanban Experience with AI-related tools and frameworks, such as TensorFlow or PyTorch Knowledge of data engineering, data warehousing, and data governance Experience with agile development methodologies, such as Scrum or Kanban Certification in data science, machine learning, or a related field Experience with leadership and mentoring, with a proven track record of guiding junior team members and helping them grow in their careers Strong business acumen, with the ability to understand business needs and develop solutions that drive business growth and improvement. Preferred Skills: Technology->Artificial Intelligence->Artificial Intelligence - ALL Technology->Machine Learning->Generative AI Technology->Machine Learning->AI/ML Solution Architecture and Design->generative ai Technology->Machine Learning->Python Additional Responsibilities: Required Qualifications: B.E/B.Tech/M.E/M.Tech/MCA degree in Computer Science, Information Technology, or a related field At least 8 years of experience in software development, with at least 2 years of experience in Generative AI Proficiency in LangChain, Python, Generative AI, Agentic AI, Kafka, and Advanced Prompt Engineering Techniques Strong understanding of software architecture, design patterns, and principles Excellent problem-solving skills, with the ability to analyze complex technical problems and develop creative solutions Strong communication and teamwork skills, with the ability to collaborate with cross-functional teams and communicate technical concepts to non-technical stakeholders Tech Skill: LangChain, Python, Fast/Flask API, Gen AI, Agentic AI, Advanced Prompt Engineering, Machine Learning, SQL, Kafka Soft Skill: Communication, Team Work, Problem Solving Educational Requirements Bachelor of Engineering Service Line Information Systems Location of posting is subject to business requirements

Job Description: We are seeking a highly skilled and passionate AI/ML Engineer with strong expertise in Generative AI and Large Language Models (LLMs) . The ideal candidate will have hands-on experience in building, fine-tuning, and deploying agentic AI systems using modern GenAI frameworks. You will work on cutting-edge projects involving prompt engineering , RAG pipelines , and memory architectures such as vector databases. Responsibilities: Design and implement AI/ML solutions using modern LLM architectures and agentic AI concepts . Build and optimize intelligent agents using frameworks such as LangChain, AutoGen, CrewAI , or Semantic Kernel . Develop and fine-tune generative AI models with Transformers , HuggingFace , OpenAI API , etc. Implement and enhance Retrieval-Augmented Generation (RAG) pipelines and memory systems like vector databases (e.g., FAISS, Pinecone). Write high-performance Python code to support experimentation, model integration, and API interactions. Collaborate cross-functionally with product, design, and engineering teams in an agile development environment. Deploy AI solutions on cloud platforms (AWS, Azure, or GCP) with a focus on scalability and performance. Stay updated with the latest advancements in the AI/ML/GenAI space. Required Experience: 3 to 8 years of experience in AI/ML , with at least 1 year in Generative AI / LLM-based projects . Proven expertise in Python programming and related libraries for ML/GenAI. Hands-on experience with one or more GenAI frameworks (LangChain, AutoGen, etc.). Solid understanding of prompt engineering , RAG , vector DBs , and agent-based systems . Cloud deployment experience (AWS, Azure, or GCP) is a must. Strong analytical and problem-solving skills.

Job Title : Senior Software Engineer. Exp: 5 Years to 10 Years Location : Remote. About the Company: Galileo is the leading platform for Gen AI evaluation and observability, with a mission to democratize building safe, reliable and robust applications in the new era of AI powered software development. Our foundation is built on pioneering the early technology behind the world's most ubiquitous AI applications including Apple's Siri and Google Speech. We firmly believe that AI developers require meticulously crafted, research-driven tools to create trustworthy and high-quality generative AI applications that will revolutionize our work and lifestyle. Galileo addresses the complexities inherent in implementing, evaluating, and monitoring GenAI applications, optimizing the development process for both individual developers and teams by offering a comprehensive platform that spans the full AI development lifecycle. Galileo bridges critical gaps, significantly enhancing developers' ability to refine and deploy reliable and precise GenAI applications. Since its inception, Galileo has rapidly gained traction, serving Fortune 100 banks, Fortune 50 telecom companies, as well as AI teams at prominent organizations such as Reddit and Headspace Health, among dozens of others. Galileo has AI research at its core, with the founders coming from Google and Uber where they solved challenging AI/ML problems in the Speech, Evaluation and ML Infra domains. It is now a Series B business backed by tier 1 investors including Battery Ventures, Scale Venture Partners, and Databricks Ventures, with $68M in total funding. We are headquartered in San Francisco with locations such as New York and Bangalore, India forming our areas of future growth. Responsibilities Understand GenAI at a sufficient level of curiosity and usage (beyond simple applications such as using ChatGPT such as understanding and usage of Lang Chain, Lang Graph, Crew AI, OpenAI APIs etc. Be able to quickly understand our product hosted at https://app.galileo.ai/ Have 5 years of experience working on Product Engineering teams building service oriented or general micro services-based applications using Python Can work in a fast-paced environment and can get ideas quickly off the ground with minimal support (ideally has experience working in a mix of large enterprises and startup experience). Skill Requirements Programming languages: Python and Typescript Basic understanding of LLM (OpenAI/Gemini/) API and SDK Basic understanding of AI frameworks like Langchain, CrewAI etc. Has some exposure and understanding of Observability and Reliability (such as familiarity with OTEL, understanding of SLOs) Has some degree of familiarity with Cloud environments such as Azure, GCP and AWS If you are passionate about applying your experience in the AI/ML field to an emerging and advancing field of Generative AI, this is a great opportunity for you. You will get to work on a ground breaking product poised to revolutionize the way companies approach LLM Evaluations. Join our team at Galileo and help us build the future of Evaluations in Generative AI.

Job Title: AI Developer Supply Chain Management Location: Permanent Remote Job Type: Full-time Team: Product AI Engineering We are looking for a talented LLM Developer to join our AI Engineering team and contribute to the development of the SCM Expert AI Agent the core brain behind AI capabilities like demand forecasting, anomaly detection, ETA prediction, and route optimization in the FarmToPlate (F2P) platform. In this role, you will focus on integrating and optimizing LLM-based agentic architectures using frameworks like LangChain, CrewAI, and RAG pipelines. Youll work closely with traditional ML developers and backend engineers to deploy intelligent, explainable, and real-time decision agents for supply chain management. Responsibilities: Design, build, and optimize LLM-based agents using LangChain, CrewAI, or custom wrappers. Implement RAG pipelines with vector stores (e.g., FAISS, ChromaDB) and embedding models. Develop LLM-powered tools for demand forecasting, query understanding, anomaly explanations, and summarization. Integrate agents with internal and external data sources using tools like MongoDB, Sklearn datasets, or Browsing Agents. Implement prompt engineering, agent memory, and context-chaining for more dynamic agent behavior. Collaborate with data science and product teams to translate SCM logic into agentic workflows. Expose models and agents through APIs using FastAPI, including role-based access if needed. Optimize runtime performance with quantization, PEFT (parameter-efficient finetuning), and model caching. Track experiments, versions, and deployment artifacts using tools like MLflow, SageMaker, or custom registries. Requirements: 3-5 years of experience working on Python-based AI systems. Strong understanding of LLMs, Transformers, Prompt Engineering, and conversational AI. Hands-on experience with LangChain, CrewAI, OpenAI/GPT APIs, or Hugging Face Transformers. Familiarity with RAG concepts, vector databases (FAISS, Chroma), and embedding techniques. Good knowledge of API frameworks (FastAPI/Flask) and working with JSON schema-driven inputs. Basic understanding of traditional ML models and workflows (e.g., regression, classification, anomaly detection). Comfortable integrating external data tools and APIs into LLM pipelines. Bonus Points For Experience building Agentic RAG systems that combine logic, tools, memory, and models. Knowledge of Open Source LLM tuning using PEFT, LoRA, bitsandbytes, Unsloth, etc. Familiarity with SageMaker, EKS, or deploying custom models to the cloud. Experience in supply chain/logistics, or working with ERP/SCM structured data. Built monitoring dashboards using Evidently.ai or similar model observability tools. Why Join Us Be part of a domain-driven AI platform blending supply chain expertise with modern agentic LLM architectures. Work on real-world use cases that impact farm-to-plate food systems at scale. Collaborate with a fast-moving, cross-functional team that values innovation, ownership, and outcome. Learn and grow in a modular, full-stack AI environment where your ideas become deployed APIs. Enjoy flexibility in remote, experimentation, and continuous learning.

Tech stack required: Programming languages: Python Public Cloud: AzureFrameworks: Vector Databases such as Milvus, Qdrant/ ChromaDB, or usage of CosmosDB or MongoDB as Vector stores. Knowledge of AI Orchestration, AI evaluation and Observability Tools. Knowledge of Guardrails strategy for LLM. Knowledge on Arize or any other ML/LLM observability tool. Experience: Experience in building functional platforms using ML, CV, LLM platforms. Experience in evaluating and monitoring AI platforms in production Nice to have requirements to the candidate Excellent communication skills, both written and verbal. Strong problem-solving and critical-thinking abilities. Effective leadership and mentoring skills. Ability to collaborate with cross-functional teams and stakeholders. Strong attention to detail and a commitment to delivering high-quality solutions. Adaptability and willingness to learn new technologies. Time management and organizational skills to handle multiple projects and priorities.

Required Skills 7+ years of professional Python development experience Hands-on experience with at least one agent framework (CrewAI, LangChain, LangGraph, or equivalent) Strong understanding of LLM capabilities, limitations, and prompt engineering Experience with RESTful API design and async Python (FastAPI preferred) Knowledge of vector databases and RAG (Retrieval Augmented Generation) systems Familiarity with financial or tax domains Demonstrated leadership in technical decision-making Excellent written and verbal communication skills Nice to Have Experience with AWS services, particularly Lambda and EKS Background in financial services or tax preparation software Knowledge of security and compliance requirements for financial data Previous startup experience, particularly in MVP development

We are seeking a skilled, motivated, and quick-learner Full Stack Developer to join our team working on cutting-edge Gen AI development work. The successful candidate will be responsible for developing innovative applications and solutions using including frontend and backend. While the solutions will often utilize Retrieval Augmented Generation (RAG), Agentic frameworks the role will not be limited to this, and will involve various AI technologies. Develop and maintain web applications using Angular, NDBX frameworks, and other modern technologies. Design and implement databases in Postgres DB, apply & implement ingestion and retrieval pipelines using pgvector, neo4j, ensuring efficient and secure data practices. Use different generative AI models & frameworks such as LangChain, Haystack, LlamIndex etc for chucking, embeddings, chat completions, integration with different data sources etc. Familiarity and experience with different agentic frameworks and technique like Langgraph, AutoGen, CrewAI, tool using techniques like MCP (Model Context Protocol). Use Azure & AWS cloud platforms in implementation to stay relevant to company AI guidelines requirements. Usage of OpenAPI standards, API first approach to develop APIs for communication between different software components. Collaborate with the team members to integrate various GenAI capabilities into the applications, including but not limited to RAG. Write clean, maintainable, and efficient code that adheres to company standards. Conduct testing to identify and fix bugs or vulnerabilities. Use collaboration and versioning tools such as GitHub for effective team working and code management. Stay updated with emerging technologies and apply them into operations and activities. Show a strong desire for continuous learning and the ability to quickly adapt and implement new technologies. Bachelor's degree in Computer Science, Information Technology, or a related field with 6+ years of working experience. Proven experience as a Full Stack Developer or similar role in designing, developing and deploying end to end applications. Knowledge of multiple front-end languages and libraries (e.g. HTML/ CSS, JavaScript, XML, jQuery). Experience with Angular and NDBX frameworks. Good experience with database technology such as Postgres DB, vector databases. Experience developing APIs following the OpenAPI standards. Understanding & experience in various generative AI models on cloud platforms such as Azure/ AWS, including Retrieval Augmented Generation, Prompt engineering, Agentic RAG, Agentic frameworks, Model context protocols etc. Experience with collaboration and versioning tools such as GitHub Experience with docker images, containers to package up an application with all the parts it needs, such as libraries and other dependencies, and ship it all out as one package. Functional Demonstrated responsiveness and accuracy Strong collaboration and teamwork skills Behaviours Take Ownership & Accountability Assertiveness & Persuasiveness Great attention to detail and problem-solving skills. Self-motivated with a keen interest in learning and implementing new technologies.

Job Description & Responsibilities Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams. Qualification, Skills & Experience Good hands-on experience in Advanced Python Programming Experiences in scalable Microservice Architecture and Development Good understanding of API Development, Messaging Queues and Asynchronous Task Management Basic DevOp skills and working with Docker Experience with LangChain, LangGraph, AutoGen or CrewAI are a big plus Ability to co-work in a small team with different locations Ability to learn and understand a new Python framework

We are seeking a proficient AI/ML Engineer responsible for testing, deploying, and hosting various Large Language Models (LLMs). The role involves monitoring deployed agentic services, ensuring their optimal performance, and staying abreast of the latest advancements in AI technologies. Key Responsibilities: LLM Deployment & Hosting Evaluate, test, and deploy diverse LLMs on cloud-based and on-premise infrastructures. Optimize model performance for scalability and efficiency. Implement secure API endpoints and model-serving pipelines. Strong CI/CD skills and knowledge of CI/CD tools like Jenkins, GitHub Actions, CircleCI etc. Agentic AI Services Deploy and maintain AI agents using frameworks such as CrewAI, Agnos(Phi Data), AutoGen etc. Integrate LLMs into business workflows and automation tools. Design, monitor, and enhance agentic services for real-world applications. Monitoring & Optimization Utilize advanced observability tools to monitor model performance, latency, and cost efficiency. Implement tools like AgentOps, OpenLIT, Langfuse, and Langtrace for comprehensive monitoring and debugging of LLM applications. Develop logging, tracing, and alerting systems for deployed models and AI agents. Conduct A/B testing and gather user feedback to refine AI behavior. Address model drift and retrain models as necessary. Best Practices & Research Stay updated with the latest advancements in AI, LLMs, and agentic systems. Implement best practices for prompt engineering, reinforcement learning from human feedback (RLHF), and fine-tuning methodologies. Optimize compute costs and infrastructure usage for AI applications. Collaborate with researchers and ML engineers to integrate state-of-the-art AI techniques. Strong knowledge on version control tools like GitHub Qualifications & Skills: Proficiency with LLM frameworks such as Hugging Face Transformers, OpenAI API, or Meta AI models. Strong programming skills in Python and experience with deep learning libraries (PyTorch, TensorFlow, JAX). Experience with cloud platforms (AWS, Azure, GCP) and model deployment tools (Docker, Kubernetes, FastAPI, Ray Serve). Familiarity with vector databases (FAISS, Pinecone, Weaviate) and retrieval-augmented generation (RAG) techniques. Hands-on experience with monitoring tools such as AgentOps, OpenLIT, Langfuse, and Langtrace. Understanding of prompt engineering, LLM fine-tuning, and agent-based automation. Excellent problem-solving skills and the ability to work in a dynamic AI research and deployment team. Preferred Qualifications: Experience in reinforcement learning, fine-tuning LLMs, or training custom models. Knowledge of security best practices for AI applications. Contributions to open-source AI/ML projects or research publications in the field.

Job description Job description Job Summary: We are looking for a results-driven and innovative Data Scientist with 46 years of experience in data analysis, machine learning, and product optimization. The ideal candidate will have a strong foundation in Python, SQL, and cloud services, along with practical exposure to GenAI, LLMs, and MLOps frameworks. You will be responsible for building scalable data pipelines, developing machine learning models, and solving real-world business problems with data-driven solutions. Key Responsibilities: Design and deploy LLM-powered solutions (e.g., RAG, LangChain, Vector DB) to enhance business processes. Build and fine-tune traditional ML models (Random Forest, Decision Trees) for predictive analytics. Optimize LLM performance using LoRA fine-tuning and post-training quantization. Develop and deploy containerized AI applications using Docker and FastAPI. Collaborate with agents like CrewAI and LangSmith to automate document processing and data extraction workflows. Implement Python & SQL-based ETL pipelines for real-time data ingestion. Design dashboards and KPI monitoring tools using Metabase to enable data-driven decision-making. Create data consumption triggers and automate reporting for international stakeholders. Moderate large-scale live virtual data science classes and provide operational support. Required Skills: Programming: Python, SQL, FastAPI ML & AI: Random Forest, Decision Trees, Clustering, PCA, DL, NLP, Transformers, Gen AI Frameworks/Tools: LangChain, MLflow, Kubeflow, CrewAI, LangSmith DevOps: Docker, Git Databases: MySQL, PostgreSQL, MongoDB Cloud: AWS (S3, EC2) Visualization: Metabase Other: Experience with LLM fine-tuning and quantization Role & responsibilitiesRole & responsibilities Preferred candidate profile

Role: AI/ML Engineer Has 4+ years of work experience , with at least 2+ years directly working on Generative AI and Agentic systems Knows how to use Large Language Models (LLMs) like GPT for real applications (not just research or theory) Has worked on multi-agent systems or autonomous AI agents using tools like CrewAI, AutoGen, or similar frameworks Can write smart prompts ( prompt engineering ), build apps with LLMs, and knows how to do RAG (Retrieval-Augmented Generation) Has done fine-tuning of models and built custom AI workflows Codes well in Python Has used ML frameworks like TensorFlow or PyTorch Familiar with tools like LangChain , and cloud/data platforms like AWS or Databricks Location: Bangalore/ Mumbai Shift Timing: 12:00 PM 9:00 PM Notice Period: 30 days or less Call Anumeha @ +91 6376649769/ Alfiya @ +91 8787064649