WORK MODE: Hybrid (3 days WFO)
LOCATION: Bangalore
EXPERIENCE: 5+ YOE (minimum of 2–3 years in production LLM/agent systems)

About the role
This is a senior individual contributor role (~70% solo ownership, ~30% collaborative on high-blast-radius problems). You will own and extend production backend systems while also driving greenfield builds across the Recipe Engine, cloud infrastructure, and AI/agentic systems. You report directly to the Software Engineering Manager and join a backend team of four within a 12-person engineering org.

Core responsibilities
Design and architect complex features for autonomy, data logging, and reliability — HLDs and LLDs expected from day one
Own and extend the core backend stack powering autonomous operations at scale
Build and maintain agentic workflows for recipe creation, feedback analysis, and internal tooling
Build code-intelligence tooling for internal agents: AST-based chunking, LLM-driven graph extraction, hybrid retrieval (BM25 + graph + rerank)
Improve retrieval accuracy through chunking, embeddings, and a benchmark-driven,



eval-first approach

Required skills
Robust system design fundamentals: HLD, LLD, SOLID principles — tested directly in the interview loop
Proven experience owning production LLM/agent systems (RAG pipelines, agent loops, tool calling/MCP) — not just API wrappers
Hands-on with the retrieval data layer: vector databases, chunking strategies, embeddings, hybrid retrieval
Experience tuning and improving existing RAG/retrieval pipelines; having built from scratch is a plus, not a gate
Familiarity with AWS (primary stack)

Nice to have
Experience with knowledge graphs or graph-based retrieval (Neo4j, or equivalent)
Hands-on experience with code-intelligence/retrieval frameworks (Cognee, LangChain, LlamaIndex, Haystack, or similar)
Prior exposure to AST parsing or code-aware chunking strategies

ABOUT THE COMPANY
Our client is a fast-growing, Series A-funded robotics and AI company backed by a top-tier glob

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