Senior Gen AI/ Agentic AI Engineer

Job Title: Senior Generative AI / Agentic AI Engineer

We are hiring experienced Generative AI / Agentic AI Engineers to build enterprise-grade AI assistants, conversational platforms and intelligent self-service solutions.

The role requires strong hands-on development experience in Generative AI, RAG, Agentic AI, Python and LLM orchestration frameworks. Candidates should have practical experience building and integrating AI solutions rather than only theoretical or POC-level exposure.

Key Responsibilities

• Design and develop Generative AI and Agentic AI applications
• Build enterprise RAG pipelines for knowledge-based conversational solutions
• Develop multi-step AI workflows and agents using LangChain / LangGraph
• Integrate LLMs such as OpenAI, Anthropic Claude, Hugging Face, Amazon Bedrock or similar
• Develop backend services and integrations using Python, FastAPI and REST APIs
• Integrate vector databases/search solutions for embeddings and semantic retrieval
• Build scalable AI solutions on AWS, including serverless/API-based integrations
• Implement guardrails, evaluation, grounding and hallucination-reduction techniques
• Support deployment and productionization of enterprise GenAI applications

Mandatory Skills

• Generative AI / LLM application development
• Agentic AI / AI Agents
• RAG - Retrieval-Augmented Generation
• Python
• LangChain
• LangGraph
• FastAPI / REST APIs
• LLM integration
• Vector databases / semantic search
• AWS / cloud exposure

Good to Have

• AWS Lambda / Amazon Bedrock
• Pinecone / FAISS / ChromaDB / OpenSearch
• Microservices
• Docker / CI-CD
• MCP / tool calling / multi-agent systems
• Conversational AI / chatbot development
• BFSI / financial-services experience
• .NET exposure

Job Details

• Experience: 812 years
• Location: Manyata Tech Park, Bangalore
• Work Mode: Hybrid, 23 days per week
• Work Timing: 8:00 AM–5:00 PM
• Cab Facility: Available

Preferred Candidate

We are specifically looking for candidates who have personally designed/developed production-level RAG or Agentic AI solutions and can explain their architecture and implementation in depth.

Experience merely listing GenAI/RAG/LangChain as skills without hands-on project implementation may not be sufficient.