Senior AI Engineer

You'll be the technical owner of GenAI and agentic AI for a security SaaS product. You'll build the LLM-backed features customers use in production, not internal tools or demos. As the first and only AI voice on the team, you'll make the architecture calls yourself.

Responsibilities:

• Design, build and ship RAG pipelines and multi-agent systems in production.
• Build Python/FastAPI backend services that serve LLM features to enterprise customers.
• Build and integrate MCP servers and tool-calling workflows.
• Set up evaluation and observability for LLM outputs, with eval running in CI/CD.
• Work directly with the founders and take ownership with minimal spec.

Requirements:

• Python with FastAPI or Flask as your primary backend stack.
• Hands-on experience with LangChain, LangGraph or a similar agent framework in real project work.
• A RAG pipeline you personally built, with a vector DB (Pinecone, Qdrant, Milvus, FAISS, PGVector or ChromaDB).
• 10+ years of total engineering experience.
• 3+ years of hands-on GenAI/LLM work in production.
• Experience at an enterprise SaaS product company (not services or consulting).
• Based in Bengaluru, or willing to relocate for 5 days a week in the office.
• Actively looking for a change.

Good to have:

• MCP built or integrated in production.
• RAGAS, DeepEval or LangSmith for evaluation.
• Security, identity or compliance domain exposure.
• Early-stage startup or 0-to-1 build experience.
• AWS Bedrock or Google Vertex AI.
• Multi-agent frameworks (AutoGen, CrewAI, Semantic Kernel, ADK).

Skills

FastAPI, Flask, Python, RAG, Retrieval-Augmented Generation