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.

EDUCATIONAL REQUIREMENTS: · Bachelor’s or master’s degree in computer science, Information Technology , or related field.