332 Rag Jobs

Summary: We are seeking an experienced AI Engineer with 4 to 5 years of experience to join our team. The ideal candidate will have a strong background in artificial intelligence and machine learning technologies, as well as a proven track record of developing innovative solutions. Roles and Responsibilities: - Design and develop AI algorithms and models to solve complex business problems - Implement and optimize machine learning algorithms for real-time applications - Collaborate with cross-functional teams to integrate AI solutions into existing systems - Conduct research and stay up-to-date on the latest advancements in AI technology - Provide technical guidance and mentorship to junior team members - Participate in code reviews and contribute to the overall software development process Qualifications: - Bachelor's degree in Computer Science, Engineering, or related field - 4 to 5 years of experience in AI development - Strong programming skills in languages such as Python, Java, or C++ - Experience working with Langchain, LangGraph, and vector databases (e.g., Pinecone, ChromaDB, FAISS). - Hands-on experience with Hugging Face ecosystem including transformers etc. - Proficiency in model serving and deployment, using tools like FastAPI, Hugging Face Inference Endpoints, or AWS SageMaker for scalable and production-grade AI applications. - Strong understanding of prompt engineering, retrieval-augmented generation (RAG), and tokenization/token-level optimization. - Proven experience with fine-tuning and deploying LLMs (e.g., LLaMA, Mistral, Falcon, OpenAI, or Hugging Face Transformers). -Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn - Knowledge of cloud computing platforms such as AWS or Azure - Excellent problem-solving and analytical skills - Strong communication and teamwork abilities

Role & responsibilities 5 Years -11 Years Joining location - Pune Notice period - immediate to 60days Primary Skills Data Science, Python, Machine Learning Mandatory Skills Deep Learning/NLP, Computer Vision, Gen AI/LLM, Cloud (AWS / Azure / GCP) Core Skills Python, NLP, LLMs, Data Science Must-Have Experience with LLM-based Gen AI applications, prompt engineering, Langchain and/or Llama-index Nice-to-Have BERTopic/Topic Modelling, HuggingFace, Responsible AI concepts Preferred candidate profile

We are seeking a Software Engineer with expertise in AI/ML and Full stack development to contribute to the development of core platform features. This role involves designing, developing, and optimizing high-performance AI-driven applications, building scalable microservices, and ensuring seamless integration across AI, backend, and frontend systems. You will play a key role in developing workflow automation modules, AI-powered search engines, and scalable enterprise solutions. Skills: P1 (must to have Skills) Generative AI Expertise/ AI Agents, Agentic Workflows/ RAG/ Prompt Engineering / Advanced Python Programming / LangChain / LangGraph / Vector Databases. P2 (need to have Skills ) FastAPI, NodeJS / Intuitive UI/UX Design: Either React or Typescript or Next.js. P3 (nice to have Skills) LlamaIndex / Integration of SLM/LLMs. Required Skills Generative AI Expertise : Advanced knowledge in AI Agents, Agentic Workflows, Retrieval-Augmented Generation (RAG), and Prompt Engineering. Advanced Python Programming : Proficiency in Python, particularly for AI-driven applications, with experience in frameworks like LangChain and LangGraph. Vector Databases : Strong skills in managing and utilizing vector databases for AI solutions. FastAPI & NodeJS : Experience in building backend services using FastAPI or NodeJS. UI/UX Design : Ability to design and implement intuitive user interfaces, with beginner to intermediate proficiency in React. LlamaIndex & SLM/LLM Integration : Familiarity with LlamaIndex and expertise in integrating System Language Models/Large Language Models into applications. Preferred Education and Experience: Bachelors/masters degree in computer science, AI, Machine Learning, or related field. At least 3 years in full-stack development with a focus on AI. Proven track record leading small engineering teams and delivering complex AI-driven products. Direct client-facing experience, from requirements gathering to final delivery.

Job Title: Gen AI Developer (Azure + ML) Location: Gurugram (Work from Office / Hybrid as applicable) Experience: 5+ Years Employment Type: Full-time Job Overview: We are looking for a Generative AI Developer with strong hands-on experience in Microsoft Azure and Machine Learning to join our team in Gurugram . The ideal candidate should be proficient in building and deploying GenAI-powered applications using Azure OpenAI , along with solid experience in traditional ML pipelines . Key Responsibilities: Design and develop scalable Gen AI solutions using Azure OpenAI , Cognitive Services, and Azure ML. Build and deploy ML models for tasks like classification, regression, and recommendation. Implement RAG (Retrieval-Augmented Generation) architectures using vector databases (e.g., ChromaDB, FAISS, Azure Search). Orchestrate LLM workflows using tools like LangChain , Transformers , or LlamaIndex . Develop APIs/microservices to expose GenAI and ML capabilities for downstream integration. Collaborate with cross-functional teams including data engineers and product managers to deploy solutions in production. Ensure scalability, cost-efficiency, and security of AI/ML workloads on Azure. Must-Have Skills: Strong experience with Azure OpenAI , Azure Cognitive Services , and Azure Machine Learning Studio . Proficiency in Python , Transformers , and ML frameworks (scikit-learn, PyTorch, or TensorFlow). Experience with LangChain , embedding models , and vector search technologies. Understanding of ML lifecycle: data processing, feature engineering, model training, evaluation, and deployment. Experience building RESTful APIs for model consumption. Familiarity with version control , DevOps practices , and containerization (Docker). Nice to Have: Knowledge of prompt engineering , fine-tuning LLMs , or custom training . Exposure to MLOps tools like MLflow or DVC. Experience with Power BI , Azure Synapse , or Databricks is a plus. Prior experience working in domains like finance, retail, or legal tech. Preferred Certifications: Microsoft Certified: Azure AI Engineer Associate (AI-102) Microsoft Certified: Azure Data Scientist Associate (DP-100)

Role & responsibilities 4+ years of work experience as a Data Scientist Design and implement ML models for forecasting, classification, and clustering. Apply deep learning techniques and fine-tune models for performance optimization. Perform feature engineering and statistical analysis using Python (Pandas, NumPy). Operationalize models using ML Ops practices and deploy on cloud platforms (Azure/AWS/GCP). Strong proficiency in Python, SQL, Docker, and version control tools. Expertise in statistics, Pandas, NumPy, and ML algorithms. Experience with deep learning, feature engineering, and model fine-tuning. Familiarity with ML Ops and AI services on Azure, AWS, or GCP. Intersted Candidates can share your updated resume at jayanthbs@kpmg.com

We are seeking an experienced AI/ML Developer to design, develop, and deploy advanced machine learning, computer vision, and natural language processing (NLP) solutions. This role requires expertise in AI-driven development, automation, and deep learning to build scalable and efficient applications. Key Responsibilities: 1. Design, develop, and implement AI/ML models for real-world applications. 2. Work with computer vision technologies using OpenCV and Tesseract for image processing and OCR tasks. 3. Develop and optimize NLP models for text analysis, sentiment detection, and chatbot applications. 4. Implement Agentic AI solutions to create adaptive and autonomous AI-driven systems. 5. Utilize TensorFlow to build and fine-tune deep learning models. 6. Optimize model performance, accuracy, and scalability for production environments. 7. Integrate AI/ML solutions with web and mobile applications. 8. Process, clean, and analyze large datasets for training and validation. 9. Collaborate with cross-functional teams to align AI solutions with business objectives. 10. Stay updated with emerging advancements in AI, ML, and deep learning. Required Skills & Expertise: 1. Python Proficiency Strong programming skills in Python for AI/ML applications. 2. Computer Vision & OCR Hands-on experience with OpenCV and Tesseract. 3. NLP & Text Processing – Expertise in Natural Language Processing techniques. 4. Deep Learning – Experience with TensorFlow, model training, and neural networks. 5. Agentic AI – Understanding of AI agents, autonomous decision-making, and self-learning models. 6. Data Preprocessing & Augmentation – Ability to clean and preprocess large datasets. 7. Optimization & Deployment – Experience with model fine-tuning, GPU acceleration, and cloud deployment. 8. Version Control & CI/CD – Familiarity with Git, MLOps, and deployment pipelines. Preferred Skills: Experience with PyTorch, Hugging Face, LangChain, Reinforcement Learning, and Edge AI . Knowledge of LLMs (Large Language Models) and Generative AI .

You will be joining a company that specializes in Identity and Access Management (IAM) and Customer Identity and Access Management (CIAM), offering advanced solutions to enhance security for your workforce, customers, and partners. The company also provides cutting-edge security solutions for various popular CMS and project management platforms such as Atlassian, WordPress, Joomla, Drupal, Shopify, BigCommerce, and Magento. The solutions offered are precise, effective, and focused on improving overall security measures. As an AI/ML Engineer with our team, you will play a crucial role in developing innovative AI-powered products and solutions. The ideal candidate for this position should possess a minimum of 10 years of hands-on experience in creating and implementing advanced AI and ML models and related software systems. This is a full-time employee position based in Baner, Pune. Your responsibilities will include developing machine learning and deep learning models and algorithms to address complex business challenges, enhance processes, and improve product functionality. You will work on deploying personalized large language models (LLMs), developing systems for document parsing, named entity recognition (NER), retrieval-augmented generation (RAG), and chatbots, as well as building robust data and ML pipelines for production scalability and performance. Additionally, you will optimize machine learning models for better performance, scalability, and accuracy using techniques like hyperparameter tuning and model optimization. It is crucial to write high-quality, production-ready code using frameworks such as PyTorch or TensorFlow and stay updated on the latest advancements in AI/ML technologies and tools. To qualify for this role, you should hold a Bachelor's or Master's Degree in Computer Science, Data Science, Computational Linguistics, Natural Processing (NLP), or related fields. You must have extensive experience in developing and deploying machine learning models and algorithms, with proficiency in AI/ML frameworks such as TensorFlow, PyTorch, and scikit-learn. Strong programming skills in Python, Java, or C++ are necessary, along with familiarity with web frameworks like FastAPI, Flask, Django, and agentic AI frameworks such as LangChain, LangGraph, AutoGen, or Crew AI. Knowledge of Data Science and MLOps, including ML/DL, Generative AI, containerization (Docker), and orchestration (Kubernetes) for deployment is essential. Experience with cloud platforms like AWS, Azure, and GCP, as well as AI/ML deployment tools, is highly beneficial. In this role, you will have the opportunity to work with a team of talented individuals in a stable, collaborative, and supportive work environment. You will be constantly exposed to new technologies and have the chance to expand your skills and knowledge in the field of AI/ML. Your communication and collaboration skills will be put to the test as you collaborate with stakeholders to understand business requirements, define project objectives, and deliver AI/ML solutions that meet customer needs and drive business value.,

As a hands-on backend expert, you will be responsible for taking our FastAPI-based platform to the next level by building production-grade model-inference services, agentic AI workflows, and seamless integration with third-party LLMs and NLP tooling. Please note that this role is being hired for one of our client companies, and the company name will be disclosed during the interview process. In this role, you will have the opportunity to work on the following key areas: Core Backend Enhancements: - Build APIs - Harden security with OAuth2/JWT, rate-limiting, SecretManager, and observability with structured logging and tracing - Implement CI/CD, test automation, health checks, and SLO dashboards Awesome UI Interfaces: - Develop UI interfaces using React.js/Next.js, Redact/Context, and various CSS frameworks like Tailwind, MUI, Custom-CSS, and Shadcn LLM & Agentic Services: - Design micro/mini-services to host and route to OpenAI, Anthropic, local HF models, embeddings, and RAG pipelines - Implement autonomous/recursive agents that orchestrate multi-step chains including Tools, Memory, and Planning Model-Inference Infrastructure: - Set up GPU/CPU inference servers behind an API gateway - Optimize throughput with batching, streaming, quantization, and caching using technologies like Redis and pgvector NLP & Data Services: - Own the NLP stack focusing on Transformers for classification, extraction, and embedding generation - Build data pipelines that combine aggregated business metrics with model telemetry for analytics You will be working with the following tech stack: - Python, FastAPI, Starlette, Pydantic - Async SQLAlchemy, Postgres, Alembic, pgvector - Docker, Kubernetes, or ECS/Fargate on AWS or GCP - Redis, RabbitMQ, Celery for jobs and caching - Prometheus, Grafana, OpenTelemetry - HuggingFace Transformers, LangChain, Torch, TensorRT - OpenAI, Anthropic, Azure OpenAI, Cohere APIs - Pytest, GitHub Actions - Terraform or CDK To be successful in this role, you must have: - 3+ years of experience building production Python REST APIs using FastAPI, Flask, or Django-REST - Strong SQL schema design and query optimization skills in Postgres - Deep knowledge of async patterns and concurrency - Hands-on experience with UI applications that integrate with backend APIs - Experience with RAG, LLM/embedding workflows, prompt-engineering, and agent-ops frameworks - Cloud container orchestration experience - Proficiency in CI/CD pipelines and infrastructure-as-code Nice-to-have experience includes familiarity with streaming protocols, NGINX Ingress, RBAC, multi-tenant SaaS security, data privacy, event-sourced data models, and more. This role is crucial as our products are live and evolving rapidly. You will have the opportunity to own systems end-to-end, scale AI services, work closely with the founder, and shape the future of our platform. If you are seeking meaningful ownership and enjoy working on challenging, forward-looking problems, this role is perfect for you.,

The Implementation Technical Architect role focuses on designing, developing, and deploying cutting-edge Generative AI (GenAI) solutions using the latest Large Language Models (LLMs) and frameworks. Your responsibilities include creating scalable and modular architecture for GenAI applications, leading Python development for GenAI applications, building tools for automated data curation, integrating solutions with cloud platforms like Azure, GCP, and AWS, applying advanced fine-tuning techniques to optimize LLM performance, establishing LLMOps pipelines, ensuring ethical AI practices, implementing Reinforcement Learning with Human Feedback and Retrieval-Augmented Generation techniques, collaborating with front-end developers, and more. Key Responsibilities: - Design and Architecture: Create scalable and modular architecture for GenAI applications using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Python Development: Lead the development of Python-based GenAI applications, ensuring high-quality, maintainable, and efficient code. - Data Curation Automation: Build tools and pipelines for automated data curation, preprocessing, and augmentation to support LLM training and fine-tuning. - Cloud Integration: Design and implement solutions leveraging Azure, GCP, and AWS LLM ecosystems, ensuring seamless integration with existing cloud infrastructure. - Fine-Tuning Expertise: Apply advanced fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLM performance for specific use cases. - LLMOps Implementation: Establish and manage LLMOps pipelines for continuous integration, deployment, and monitoring of LLM-based applications. - Responsible AI: Ensure ethical AI practices by implementing Responsible AI principles, including fairness, transparency, and accountability. - RLHF and RAG: Implement Reinforcement Learning with Human Feedback (RLHF) and Retrieval-Augmented Generation (RAG) techniques to enhance model performance. - Modular RAG Design: Develop and optimize Modular RAG architectures for complex GenAI applications. - Open Source Collaboration: Leverage Hugging Face and other open-source platforms for model development, fine-tuning, and deployment. - Front-End Integration: Collaborate with front-end developers to integrate GenAI capabilities into user-friendly interfaces. Required Skills: - Python Programming: Deep expertise in Python for building GenAI applications and automation tools. - LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain. - Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data. - Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models. - Fine-tune SLM(Small Language Model) for domain specific data and use cases. - Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc. - Anti-hallucination and anti-gibberish tools such as Bleu etc. - Cloud Platforms: Extensive experience with Azure, GCP, and AWS LLM ecosystems and APIs. - Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. - LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management. - Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations. - RLHF and RAG: Advanced skills in Reinforcement Learning with Human Feedback and Retrieval-Augmented Generation. - Modular RAG: Deep understanding of Modular RAG architectures and their implementation. - Hugging Face: Proficiency in using Hugging Face and similar open-source platforms for model development. - Front-End Integration: Knowledge of front-end technologies to enable seamless integration of GenAI capabilities. - SDLC and DevSecOps: Strong understanding of secure software development lifecycle and DevSecOps practices for LLMs.,

You will be responsible for designing, building, and deploying scalable NLP/ML models for real-world applications. Your role will involve fine-tuning and optimizing Large Language Models (LLMs) using techniques like LoRA, PEFT, or QLoRA. You will work with transformer-based architectures such as BERT, GPT, LLaMA, and T5, and develop GenAI applications using frameworks like LangChain, Hugging Face, OpenAI API, or RAG (Retrieval-Augmented Generation). Writing clean, efficient, and testable Python code will be a crucial part of your tasks. Collaboration with data scientists, software engineers, and stakeholders to define AI-driven solutions will also be an essential aspect of your work. Additionally, you will evaluate model performance and iterate rapidly based on user feedback and metrics. The ideal candidate should have a minimum of 3 years of experience in Python programming with a strong understanding of ML pipelines. A solid background and experience in NLP, including text preprocessing, embeddings, NER, and sentiment analysis, are required. Proficiency in ML libraries such as scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers, and spaCy is essential. Experience with GenAI concepts, including prompt engineering, LLM fine-tuning, and vector databases like FAISS and ChromaDB, will be beneficial. Strong problem-solving and communication skills are highly valued, along with the ability to learn new tools and work both independently and collaboratively in a fast-paced environment. Attention to detail and accuracy is crucial for this role. Preferred skills include theoretical knowledge or experience in Data Engineering, Data Science, AI, ML, RPA, or related domains. Certification in Business Analysis or Project Management from a recognized institution is a plus. Experience in working with agile methodologies such as Scrum or Kanban is desirable. Additional experience in deep learning and transformer architectures and models, prompt engineering, training LLMs, and GenAI pipeline preparation will be advantageous. Practical experience in integrating LLM models like ChatGPT, Gemini, Claude, etc., with context-aware capabilities using RAG or fine-tuning models is a plus. Knowledge of model evaluation and alignment, as well as metrics to calculate model accuracy, is beneficial. Data curation from sources for RAG preprocessing and development of LLM pipelines is an added advantage. Proficiency in scalable deployment and logging tooling, including skills like Flask, Django, FastAPI, APIs, Docker containerization, and Kubeflow, is preferred. Familiarity with Lang Chain, LlamaIndex, vLLM, HuggingFace Transformers, LoRA, and a basic understanding of cost-to-performance tradeoffs will be beneficial for this role.,

Join our high-growth product engineering team to contribute to building next-gen B2C platforms that cater to millions of users. We are seeking a tech-savvy leader with over 5 years of experience in backend architecture, scalable systems, and fast-paced product development. This is a hybrid role that combines technical depth with a strong product mindset. As a part of our team, you will be responsible for designing and developing scalable backend services utilizing Java (Spring Boot) and Python (FastAPI/Django). You will be involved in making architectural decisions related to cloud infrastructure, real-time data pipelines, and AI-powered systems. Collaboration with product, design, and DevOps teams will be key to deliver high-impact features that enhance user experience. The ideal candidate should demonstrate proficiency in Java and Python frameworks such as Spring Boot, Django, or FastAPI. Hands-on experience with microservices, streaming data pipelines, and event-driven architecture is essential. A strong working knowledge of Redis, PostgreSQL, PGVector, and cloud platforms like AWS or GCP is required. Exposure to AI/ML tools such as GPT, RAG, vector databases, and chatbot frameworks is a plus. Additionally, the ability to lead design reviews, mentor junior developers, and establish engineering best practices is highly valued. Bonus points will be awarded for experience in building or scaling significant B2C platforms, familiarity with frontend technologies like ReactJS for rapid dashboard development, and knowledge of containerization, CI/CD, and observability tools such as Grafana, Prometheus, OTEL. This position is based in Thane, Maharashtra, and offers a hybrid/on-site work mode.,

As a Senior QA Engineer at our company, you will be leading quality assurance for Generative AI (GenAI) solutions within our Digital Twin platform. Your role will involve focusing on the evaluation, reliability, and guardrails of AI-powered systems in production, going beyond traditional QA practices. Your responsibilities will include designing and implementing end-to-end QA strategies for applications using Node.js integrated with LLMs, RAG, and Agentic AI workflows. You will establish benchmarks and quality metrics for GenAI components, develop evaluation datasheets for LLM behavior validation, and conduct data quality testing for RAG databases. Additionally, you will perform A/B testing, define testing methodologies, collaborate with developers and AI engineers, build QA automation, and lead internal capability development by mentoring QA peers on GenAI testing practices. To be successful in this role, you should have at least 6 years of experience in software quality assurance, with a minimum of 3 years of experience in GenAI or LLM-based systems. You should possess a deep understanding of GenAI quality dimensions, experience in creating and maintaining LLM evaluation datasets, and familiarity with testing retrieval pipelines and RAG architectures. Preferred skills include experience with GenAI tools/platforms, exposure to evaluating LLMs in production settings, familiarity with prompt tuning and few-shot learning in LLMs, and basic scripting knowledge in Python, JavaScript, or TypeScript. If you are a passionate and forward-thinking QA Engineer with a structured QA discipline, hands-on experience in GenAI systems, and a strong sense of ownership, we encourage you to apply for this high-impact role within our innovative team.,

Title : GenAI Engineer Experience : 5+ Years (Relevant) No. Of Positions : 5 Location : Remote Mandatory Skills : Python, Langraph/Langchain, AWS, EKS, CICD, RAG, LLM. 5x GenAI Platform: Support BAU (recently onboarded projects), build out platform, experienced engineer, platform thinking, Python, Java, EKS, ideally GenAI o Understand RAG, LLMs, etc - To the level they're able to help build. o Experience working on GenAI platform projects.

Were Hiring! AI/ML Intern. Are you passionate about artificial intelligence and looking to kickstart your career in machine learning? Join EICE as an AI/ML Intern and get hands-on experience working on real-world challenges in machine learning, generative AI, and advanced domains like LLMs, GenAI, and retrieval-augmented generation (RAG/REAG). What youll work on: 1. Intelligent system development 2. Generative AI & data-driven solutions 3. Data preprocessing, model development & deployment 4. Cutting-edge projects using advanced AI technologies Internship Mode : onsite

Roles and Responsibilities Lead a team of AI developers to design, develop, and deploy large language models (LLM) solutions using OpenAI's RAGBank. Collaborate with cross-functional teams to identify business requirements and translate them into technical specifications for LLM development. Develop and maintain high-quality codebase for deployed LLM models, ensuring scalability, reliability, and performance. Participate in code reviews to ensure adherence to coding standards and best practices. Provide guidance on data preprocessing techniques for text data ingestion from various sources. Desired Candidate Profile 5-10 years of experience in developing AI/ML applications with expertise in LLMs. Strong understanding of OpenAI's RAGBank architecture and its application in natural language processing tasks. Proficiency in programming languages such as Python or similar technologies; knowledge of TensorFlow or PyTorch is an added advantage.

Greetings!!! This is in regards to a Job opportunity for AI Lead - Agentic AI & RAG with Datamatics Global Services Ltd. Position: AI Lead - Agentic AI & RAG Website: https://www.datamatics.com/ Job Location: Mumbai/Bangalore Job Description: Seeking a skilled AI Engineer to design and deliver a scalable, secure, and intelligent chatbot solution built entirely on the Microsoft Azure ecosystem. The solution will leverage Azure OpenAI, Azure Foundry, and Azure Cognitive Search to power a guided buying assistant with enterprise-grade compliance and AI-driven intelligence. Key Responsibilities & Required Expertise: 1.Deep hands-on experience with Retrieval-Augmented Generation (RAG) using Azure Cognitive Search and Azure Cosmos DB, including embedding generation, chunking, indexing, and semantic retrieval. 2.Strong knowledge of agentic AI design using Semantic Kernel, including task planning, tool/function calling, memory management, and autonomous reasoning flows. 3.Proven experience implementing multi-turn conversational agents using Azure OpenAI Service (GPT-4/4o) in inference-only mode, with secure prompt and session management. 4.Skilled in designing and optimizing prompt engineering strategies including system messages, dynamic templating, and user intent extraction. 5.Familiarity with Azure AI Studio and Azure Machine Learning for managing model deployments, testing, and monitoring. 6.Strong understanding of embedding models within Azure (e.g., text-embedding-ada-002 or Foundry-specific embeddings) for knowledge base enrichment and document understanding. 7. Expertise in building secure, compliant AI systems aligned with SOC 2, GDPR, and enterprise RBAC standards, ensuring no client data is used for training or fine-tuning. 8. Proficiency in Python, particularly with Azure SDKs, Semantic Kernel, and REST APIs for integrating AI into enterprise workflows. 9. Experience embedding AI-driven workflows into Azure-hosted applications, including React JS frontends and OutSystems low-code environments. 10. Ability to collaborate closely with architects, product managers, and UX teams to translate procurement workflows into intelligent assistant behavior.

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

Role: We are seeking an experienced and innovative Senior Full Stack Developer with at least 5 years of expertise in Python and front-end frameworks such as React. The ideal candidate will possess deep knowledge of AI integration, agent-based system development, and a passion for delivering sophisticated, scalable applications. You will play a crucial role in designing, developing, and maintaining our cutting-edge agentic AI platform. Responsibilities: Your Major Job responsibilities, but not limited to, shall be as under: Design, develop, and maintain scalable and robust full-stack applications using Python (backend) and React (frontend) . Architect and build intelligent AI-driven agents , integrating advanced AI capabilities such as natural language processing , retrieval-augmented generation (RAG) , and machine learning models . Collaborate closely with cross-functional teams including product managers, data scientists, and UX designers to implement comprehensive product solutions. Ensure the responsiveness, reliability, and security of web applications deployed across cloud environments. Lead and mentor junior developers , conducting code reviews and ensuring adherence to best practices in software engineering. Qualifications & Requirements: Minimum of 5 years of experience as a Full Stack Developer. Expert-level proficiency in Python and hands-on experience with frameworks such as Django, Flask, or FastAPI. Strong front-end development skills, particularly with React and related technologies (Redux, Hooks, Context API). Demonstrated expertise in AI technologies, including natural language processing, embeddings, retrieval-augmented generation (RAG), and large language models (LLMs). Experience designing and implementing autonomous AI agents or similar intelligent systems. Familiarity with databases (PostgreSQL, MongoDB, vector databases), cloud platforms (AWS, Azure, Google Cloud), and containerization technologies (Docker, Kubernetes). Exceptional problem-solving abilities, communication skills, and a proven track record of delivering high-quality software products. Preferred Qualification: Prior experience in developing enterprise-grade AI solutions. Familiarity with agentic frameworks and protocols. Contributions to open-source AI or web projects.

As an AI Software Engineer at DHL IT Services, you will be part of a global team of over 5600 IT professionals dedicated to connecting people and driving the global economy through continuous innovation and sustainable digital solutions. Your role will involve shaping the technology backbone of the world's largest logistics company, pushing boundaries across all dimensions of logistics. At DHL IT Services, we prioritize digitalization and are committed to providing exceptional employee experiences as reflected in our #GreatPlaceToWork certification. You will play a crucial role as an AI Engineer, serving as a pathfinder for the Engineering team. Your responsibilities will include understanding on-ground challenges and devising solutions to enhance efficiency in delivering solutions for faster time-to-market. Proficiency in leveraging AI tools for real-world use cases and improving productivity will be essential. To excel in this role, you must have experience in Python, Prompt Engineering, Generative AI models, and AI use cases application. Knowledge of AI workflow tools like LangChain and n8n will be advantageous in enhancing our business and IT processes for better efficiency. Your ability to break down tasks to use the appropriate learning models and ensure high-quality results through context engineering using RAG and MCP protocols is crucial. Working independently and effectively prioritizing and organizing tasks under time and workload pressure are key skills required for this role. You can expect to collaborate with multinational teams across the globe, making proficiency in spoken and written English highly valuable. In addition to a challenging and rewarding work environment, we offer a range of benefits including hybrid work arrangements, generous annual leave, comprehensive medical insurance coverage for you, your spouse, and children, as well as opportunities for in-house training programs and professional certifications. Join us on this exciting journey to drive innovation and digital transformation in the logistics industry. #DHL #DHLITServices #GreatPlace,

What will you do Voice AI Stack Ownership: Build and own the end-to-end voice bot pipeline ASR, NLU, dialog state management, tool calling, and TTS to create a natural, human-like conversation experience. LLM Orchestration & Tooling: Architect systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implement retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Design scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineer low-latency, streaming ASR + TTS pipelines and fine-tune turn-taking models for natural conversation. Model Tuning & Hallucination Control: Use fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Build robust observability, run real-time call QA pipelines, and analyze interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Work closely with product, infra, and leadership to scale this bot to thousands of US dealerships. What will make you successful in this role Architect-level thinking: You understand how ASR, LLMs, memory, and tools fit together and can design modular, observable, and resilient systems. LLM Tooling Mastery: You've implemented tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: You know how to chunk, embed, index, and retrieve and how to avoid prompt bloat and token overflow. Latency-First Mindset: You debug token delays, know the cost of each API hop, and can optimize round-trip time to keep calls human-like. Grounding > Hallucination: You know how to trace hallucinations back to weak prompts, missing guardrails, or lack of tool access and fix them. Prototyper at heart: You're not scared of building from scratch and iterating fast, using open-source or hosted tools as needed. What you must have 5+ years in AI/ML or voice/NLP systems with real-time experience Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models Solid understanding of latency optimization, streaming inference, and real-time audio pipelines Hands-on with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP) Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior

You are an experienced Lead Data Scientist with a minimum of 8 years of professional experience, including at least 6 years in a data science role. Your expertise lies in statistical modeling, machine learning, deep learning, and GenAI. Proficiency in Python is a must, along with hands-on experience in optimizing code for performance. You excel in data preprocessing, feature engineering, data visualization, hyperparameter tuning, and have a solid understanding of database concepts, especially while working with large datasets. You have experience deploying and scaling machine learning models in a production environment, along with familiarity with machine learning operations (MLOps) and related tools. Your knowledge extends to Generative AI concepts and LLM finetuning, supported by excellent communication and collaboration skills. Your responsibilities as a Lead Data Scientist include guiding and mentoring a high-performance team on the latest technology landscape, patterns, and design standards. You provide strategic direction and technical leadership for AI initiatives, leading the design and architecture of complex AI systems. Your role involves developing and deploying machine learning/deep learning models to address key business challenges, applying various techniques in statistical modeling, data preprocessing, feature engineering, and more. You are proficient in areas such as computer vision, predictive analytics, natural language processing, time series analysis, and recommendation systems. Furthermore, you design and optimize data pipelines for model training and deployment, utilizing model serving frameworks and APIs for integration with other systems. Your qualifications include a Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Your primary skills encompass Python, Data Science concepts, Pandas, NumPy, Matplotlib, Artificial Intelligence, Statistical Modeling, Machine Learning, Natural Language Processing (NLP), Deep Learning, Model Serving Frameworks, MLOps, Computer Vision, Predictive Analytics, Time Series Analysis, Anomaly Detection, Recommendation Systems, Generative AI, and proficiency in Cloud Computing Platforms. Your secondary skills involve expertise in designing scalable and efficient model architectures, the ability to assess and forecast financial requirements of data science projects, and strong communication skills for conveying technical concepts to stakeholders. As a Lead Data Scientist, you stay updated with the latest advancements in data science and machine learning, particularly in generative AI, to evaluate their potential applications and serve as a primary point of contact for client managers.,

As a Senior AI Engineer - Voice AI / Autonomous Agents at Spyne, you will have the opportunity to own and build Spynes in-house voice bot stack. In this high-impact individual contributor role, you will be at the intersection of LLMs, ASR/TTS, and voice UX, focusing on creating deeply human, latency-optimized conversations between auto dealerships and their customers. Your main responsibilities will include: Voice AI Stack Ownership: Building and owning the end-to-end voice bot pipeline, including ASR, NLU, dialog state management, tool calling, and TTS to deliver a natural, human-like conversation experience. LLM Orchestration & Tooling: Architecting systems using MCP (Model Context Protocol) to mediate structured context between real-time ASR, memory, APIs, and the LLM. RAG Integration: Implementing retrieval-augmented generation to ground responses using dealership knowledge bases, inventory data, recall lookups, and FAQs. Vector Store & Memory: Designing scalable vector-based search for dynamic FAQ handling, call recall, and user-specific memory embedding. Latency Optimization: Engineering low-latency, streaming ASR + TTS pipelines and fine-tuning turn-taking models for natural conversation. Model Tuning & Hallucination Control: Using fine-tuning, LoRA, or instruction tuning to customize tone, reduce hallucinations, and align responses to business goals. Instrumentation & QA Looping: Building robust observability, running real-time call QA pipelines, and analyzing interruptions, hallucinations, and fallbacks. Cross-functional Collaboration: Working closely with product, infra, and leadership to scale this bot to thousands of US dealerships. To be successful in this role, you should possess: Architect-level thinking: Understanding how ASR, LLMs, memory, and tools fit together and having the ability to design modular, observable, and resilient systems. LLM Tooling Mastery: Implementing tool calling, retrieval pipelines, function calls, or prompt chaining across multiple workflows. Fluency in Vector Search & RAG: Knowing how to chunk, embed, index, and retrieve, while avoiding prompt bloat and token overflow. Latency-First Mindset: Debugging token delays, understanding the cost of each API hop, and optimizing round-trip time to maintain human-like interactions. Grounding > Hallucination: Tracing hallucinations back to weak prompts, missing guardrails, or lack of tool access and effectively addressing them. Prototyper at heart: Being unafraid of building from scratch and iterating quickly, utilizing open-source or hosted tools as necessary. The ideal candidate will have: 5+ years of experience in AI/ML or voice/NLP systems with real-time experience. Deep knowledge of LLM orchestration, RAG, vector search, and prompt engineering. Experience with MCP-style architectures or structured context pipelines between LLMs and APIs/tools. Experience integrating ASR (Whisper/Deepgram), TTS (ElevenLabs/Coqui), and OpenAI/GPT-style models. Solid understanding of latency optimization, streaming inference, and real-time audio pipelines. Hands-on experience with Python, FastAPI, vector DBs (Pinecone, Weaviate, FAISS), and cloud infra (AWS/GCP). Strong debugging, logging, and QA instincts for hallucination, grounding, and UX behavior. Working at Spyne offers real-world AI impact at scale, a high-performing team that balances speed with technical depth, high autonomy and visibility from day one, rapid career acceleration, access to MacBook and all necessary tools and compute, a flat structure with real work focus, and no BS. Join us in redefining how cars are marketed and sold with cutting-edge Generative AI.,

As a Full-Stack AI App Developer at EMO Energy, you will play a key role in reimagining urban mobility, energy, and fleet operations through our AI-driven super app. You will have the opportunity to take full ownership of building and deploying a cutting-edge energy infrastructure startup in India. Your responsibilities will include architecting and developing a full-stack AI-enabled application, designing modular frontend views using React.js or React Native, creating intelligent agent interfaces, building secure backend APIs for managing energy and fleet operations, integrating real-time data workflows, implementing fleet tracking dashboards, and optimizing performance across various platforms. Collaboration with the founding team, ops team, and hardware teams will be essential to iterate fast and solve real-world logistics problems. The ideal candidate for this role should have a strong command of front-end frameworks such as React.js, experience with back-end technologies like FastAPI, Node.js, or Django, proficiency in TypeScript or Python, familiarity with GCP services, Docker, GitHub Actions, and experience with mobile integrations and AI APIs. End-to-end ownership of previous applications, strong UI/UX product sensibility, and experience in building dashboards or internal tools will be valuable assets. Additionally, the ability to adapt to ambiguity, communicate technical decisions to non-engineers, and a passion for clean code and impactful work are crucial for success in this role. If you are a highly motivated individual with a passion for AI-driven applications and a desire to lead the development of a cutting-edge fleet/energy platform, then this role at EMO Energy is the perfect opportunity for you. Join us in revolutionizing the future of urban mobility and energy infrastructure in India.,

As an AI Developer, you will be responsible for designing and developing AI/ML models focused on natural language understanding, intelligent automation, and real-time decision-making utilizing NLP, LLMs, and RAG techniques. Your role will involve collaborating with cross-functional teams to seamlessly integrate AI models into platforms, ensuring scalability, accuracy, and efficiency. Additionally, you will support training and development programs across various locations in India, including client sites, academic institutions, and partner locations. Your responsibilities will include the continuous testing, refinement, and documentation of AI systems using tools such as Python, TensorFlow, Hugging Face, and cloud services. You will also be expected to engage in knowledge sharing activities, conduct technical workshops, and deliver on-site demos to promote AI solutions and drive adoption. This is a full-time position with benefits including cell phone reimbursement, provided meals, health insurance, paid sick time, and Provident Fund. The work schedule is during day shift hours. The ideal candidate should hold a Bachelor's degree and have a total of 1 year of experience, with specific experience as an AI Developer preferred. The work location for this role is in person. Join us in this exciting opportunity to contribute to cutting-edge AI projects and make a meaningful impact in the field of artificial intelligence.,

As an AI Specialist at our company based in Hyderabad, you will be responsible for training and fine-tuning LLMs such as LLaMA and Mistral to cater to company-specific use cases. You will play a vital role in customizing and optimizing model performance for seamless production deployment. Collaboration with internal teams for model integration and data pipelines will be a key aspect of your role. It is imperative that you stay abreast of the latest advancements in GenAI and LLM techniques to contribute effectively. To excel in this role, you must possess hands-on experience with LLMs and fine-tuning techniques. Your expertise in the specifics of vector database indexing will be highly beneficial. We are looking for someone with a robust background in advanced AI/ML techniques and database indexing, particularly in the context of production projects. Familiarity with technologies such as LoRA, QLoRA, RAG, and PEFT is desirable. Additionally, your knowledge of model evaluation, optimization, and GPU training will be crucial for success in this position.,