Lead AI Engineer

We are looking for a Lead Agentic AI Engineer who can take ownership of designing and building production-grade Agentic AI systems from architecture through deployment. You will work on AI agents capable of reasoning, planning, tool calling, retrieving domain knowledge, interacting with APIs/data sources and autonomously executing multi-step workflows. This role is ideal for someone who has moved beyond building simple LLM chatbots and has hands-on experience building real-world Agentic AI / GenAI products in production. You will work closely with AI/ML engineers, software engineers, bioinformatics experts and domain stakeholders to build intelligent systems for genomics, healthcare and life-sciences workflows.

Responsibilities:

• Architect and build Agentic AI systems and multi-agent workflows for healthcare and life-sciences use cases.
• Design agents capable of planning, reasoning, tool usage, memory, retrieval and multi-step task execution.
• Build production-grade RAG pipelines over scientific literature, genomic databases, clinical knowledge and enterprise data.
• Develop agent orchestration using frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, AutoGen or equivalent.
• Build robust tool-calling and API integration layers allowing agents to interact with databases, bioinformatics pipelines, cloud services and enterprise applications.
• Develop AI workflows for use cases such as variant interpretation, phenotype matching, genomic QC, literature mining, biomarker discovery and scientific research. Work with structured and unstructured data including genomic, clinical, scientific and multi-omics datasets.
• Integrate LLMs from providers such as OpenAI, Anthropic, Gemini or equivalent into production applications.
• Build evaluation frameworks to measure agent accuracy, hallucination, reasoning quality, latency, cost and reliability.
• Implement LLM observability, tracing, monitoring and evaluation using tools such as LangSmith, Arize, Phoenix or equivalent.
• Design mechanisms for human-in-the-loop review, guardrails, explainability and auditability, especially for healthcare/clinical workflows.
• Build scalable backend services and APIs using Python, FastAPI and modern cloud-native technologies.
• Collaborate with bioinformatics and domain experts to translate scientific problems into AI-driven workflows.
• Mentor engineers and establish engineering best practices for Agentic AI development and production deployment.
• Own the complete lifecycle from POC architecture development to evaluation and production monitoring.