Agentic AI - Pan India

Role : Gen-AI / Agentic AI Automation Engineer Location : Pune , Kolkata , Bangalore Eligibility: Education: B.Tech/B.E./M.Tech in in Computer Science, Engineering, Data Science, or a related field, or equivalent professional experience. Work Experience: 4-6 years of hands-on experience in software development, with at least 2-3 years focused on Agentic AI or GenAI technologies. Experience in Hands-on code development using GenAI / Agentic AI tools to design, build, and deploy enterprise-grade AI solutions powered by one or more of the following LLMs like GPT-4, Anthropic Claude, Mistral, using Google Vertex AI/Deep Mind, Azure OpenAI, AWS Bedrock, Azure AI Foundry, etc. Must have strong understanding of Retrieval-Augmented Generation (RAG), Embeddings, Prompt Engineering, Semantic Search, Vector Databases. Must have strong Python development expertise and practical experience implementing GenAI applications, agent orchestration frameworks like LangGraph, LangChain, AutoGen,CrewAI, etc, vector search technologies, and cloud-native AI solutions using OpenSearch, Pinecone, Chroma, Azure AI Search, pgvector, etc Must have in-depth understanding of Datawarehousing and datalake concepts and experience in developing autonomous ETL/Pipeline and orchestration of backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices. Experience working with structured and unstructured data sources, including documents, PDFs, APIs, databases, and knowledge repositories. Exposure to Agile development processes. Implement and optimize prompt engineering techniques to enhance AI model performance. Working knowledge of cloud environments such as AWS, Azure, or Google Cloud. Write clean, maintainable, and efficient code adhering to coding standards. Support debugging, performance tuning, and deployment of GenAI solutions in cloud environments. Stay updated with the latest advancements in GenAI and contribute to continuous improvement. Knowledge of Docker, Kubernetes, CI/CD, and software engineering best practices. Certification in Python, AI/ML, or cloud technologies like Azure AI, Deeplearning.AI is good to have. Mandatory Skills : Python, SQL, Data Engineering (ADF , Databricks), Generative AI Copilot, LangGraph / CrewAI / and MCP Key Responsibilities: Design and develop GenAI solutions using LLMs, RAG, tool calling, and agent-based architectures. Build and orchestrate multi-agent workflows, including planner, retriever, executor, validator, and human-in-the-loop patterns. Develop backend services and APIs using Python, FastAPI, Flask, REST APIs, and microservices. Design and implement document ingestion, embedding generation, vector indexing, reranking, and retrieval pipelines. Integrate AI applications with enterprise systems, APIs, databases, document repositories, and cloud services. Deploy, monitor, and support GenAI applications using Docker, Kubernetes, CI/CD pipelines, and cloud platforms. Implement LLMOps best practices, including model evaluation, prompt management, monitoring, logging, observability, and cost optimization. Collaborate with business and technology stakeholders to deliver scalable AI solutions that generate measurable business outcomes.