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Niche agentic LLM production skills reduce candidate pool despite early-mid experience and metro location.
Highly specialized agentic LLM and RAG production skills limit cross-industry transferability.
Many mandatory niche technical requirements and explicit 2–3 year experience strictly filter candidates.
Design, build, and ship production-grade multi-agent AI systems that operate autonomously and deliver measurable business outcomes.
Architect agent pipelines, build MCP servers, design RAG systems, and manage LLM costs at scale in a hands-on engineering capacity.
Iterate and improve systems through direct interaction with real users and clients, owning the system end-to-end from design to production.
2–3 years of relevant experience in AI system engineering or equivalent.
Graduation in Computer Science or related field.
Hands-on experience with production multi-agent systems using frameworks like LangGraph, CrewAI, or AutoGen, including agent orchestration and debugging production failures.
Proficiency in Python, FastAPI, async programming, and experience deploying AI systems with observability tooling.
Experienced in multi-agent orchestration patterns with in-depth knowledge of state schema design and human-in-the-loop workflows.
Skilled in production-level RAG pipelines, vector databases, and LLM prompt engineering with cost optimization expertise.
Comfortable working in a lean, high-output environment with ownership of production system design, deployment, and iteration based in Ahmedabad.