Agentic AI Engineer-Delhi/NCR, Bangalore & Mumbai

Location:- Delhi/NCR, Bangalore & Mumbai ROLE SUMMARY Were looking for a hands-on Agentic AI Engineer to build, optimize, and deploy production-grade AI solutions. In this role, you will be the engine room of our AI initiatives taking architectural blueprints and turning them into scalable, functional systems. You will work across the full build lifecycle from prototyping to production collaborating with Senior Architects and data scientists to deliver AI solutions in a consulting environment. WHAT YOU'LL DO Agentic Development Build: Develop LLM-based applications and multi-step agentic workflows using frameworks such as Microsoft Agent Framework, AutoGen, LangChain, LangGraph, LlamaIndex, or CrewAIRAG Pipelines: Implement Retrieval-Augmented Generation pipelines: chunking, embedding, vector search, and re-rankingTool Use & Memory: Build agents with tool-calling, short/long-term memory, and human-in-the-loop checkpointsPrompt Engineering: Design and iterate on system prompts, chain-of-thought templates, and structured output schemasModel Fine-tuning: Execute fine-tuning and optimization tasks (Quantization, PEFT/LoRA) to adapt foundation models for specific domain tasksIntegration & Delivery APIs: Expose AI capabilities via FastAPI endpoints; integrate with client data sources and third-party APIsVector Databases: Manage embeddings and retrieval using Pinecone, Qdrant, or pgvectorMLOps & Productionization Deployment: Containerize and deploy AI services using Docker and Kubernetes on AWS / Azure cloud environments, ensuring high availability and low latencyObservability: Implement observability for AI systems using LangSmith or Arize Phoenix, tracking accuracy, hallucinations, cost, and latencyCI/CD: Maintain CI/CD pipelines for ML, ensuring automated testing (unit, contract, and model-quality tests) is integrated into the delivery workflowGuardrails & Hallucination Control: Apply output validation, guardrails, and hallucination-detection techniques to ensure reliable, production-safe AI outputsToken Optimization: Apply prompt compression, context window management, and response caching to control inference cost and latencyCollaboration Client Delivery: Work closely with Senior Architects and Engagement Managers to translate business requirements into technical tasks and working solutionsCode Quality: Write clean, modular Python; participate in peer code reviews and contribute to the teams internal library of reusable AI patterns and playbooks MUST-HAVE QUALIFICATIONS Experience: 3+ years in software engineering, data engineering, or ML; at least 1 year building LLM/Gen AI applicationsPython: Strong Python skills OOP, async programming, packaging, and testingLLM Frameworks: Hands-on experience with at least one of: LangChain, LangGraph, CrewAI, AutoGen, or LlamaIndexGen AI: Working knowledge of LLM APIs (OpenAI, Anthropic Claude, Gemini) and prompt designCloud Basics: Familiarity with AWS or Azure; comfortable with REST APIs and Git-based workflowsMLOps & Productionization: Hands-on experience deploying, monitoring, and maintaining AI systems in production Docker/Kubernetes, CI/CD pipelines, and observability tooling are non-negotiableEngineering Fundamentals: Solid SQL skills, API design experience (FastAPI/Flask), and a software engineering first approach to ML encompassing testing, modularity, and documentationEducation: B.Tech / B.E. / M.Sc. in Computer Science, Information Technology, or a related field GOOD TO HAVE Evaluation: Exposure to G-Eval, RAGAS, TruLens, or LangSmith for quantifying LLM output qualityMLOps: Basic experience with MLflow or DVC for experiment trackingStructured Outputs: Experience with Pydantic-based output parsing and function/tool callingPerformance Tuning: Knowledge of vLLM or Triton Inference Server for high-throughput model servingCertifications: AWS / Azure AI Fundamentals or equivalent cloud certification Location:- Delhi/NCR, Bangalore & Mumbai ROLE SUMMARY Were looking for a hands-on Agentic AI Engineer to build, optimize, and deploy production-grade AI solutions. In this role, you will be the engine room of our AI initiatives taking architectural blueprints and turning them into scalable, functional systems. You will work across the full build lifecycle from prototyping to production collaborating with Senior Architects and data scientists to deliver AI solutions in a consulting environment. WHAT YOU'LL DO Agentic Development Build: Develop LLM-based applications and multi-step agentic workflows using frameworks such as Microsoft Agent Framework, AutoGen, LangChain, LangGraph, LlamaIndex, or CrewAIRAG Pipelines: Implement Retrieval-Augmented Generation pipelines: chunking, embedding, vector search, and re-rankingTool Use & Memory: Build agents with tool-calling, short/long-term memory, and human-in-the-loop checkpointsPrompt Engineering: Design and iterate on system prompts, chain-of-thought templates, and st