• Familiarity with PostgreSQL, Redis, and vector stores like Chroma, Pinecone, or FAISS.

• Strong problem-solving and collaboration skills across cross-functional teams.

KEY RESPONSIBILITIES:

• Design and implement agentic architectures using leading frameworks (LangGraph, CrewAI,

AutoGen, OpenDevin, etc.).

• Translate business processes into agentic pipelines with clear task orchestration, feedback loops, and

decision nodes.

• Build scalable backend systems using Python and Node.js, integrating APIs, message queues, and

orchestration layers.

• Create and maintain multi-agent coordination patterns (planner, executor, validator, critic, etc.).

• Integrate LLMs, vector databases, and knowledge graphs into agent workflows for contextual reasoning.

• Collaborate with product and business teams to convert conceptual use cases into working AI pipelines.

• Optimize system performance, error handling, and agent autonomy using observability and telemetry

tools.

• Stay ahead of evolving open-source ecosystems in agentic AI and recommend improvements to the core

architecture.

NICE TO HAVE:

• Experience in enterprise AI automation or pharmacovigilance / life sciences domains.

• Knowledge of multi-modal agents (text, image, data).

• Exposure to AI observability tools like LangFuse, Helicone, or Phoenix