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AI / LLM Lead

AI / LLM Lead

Geektrust.comPune
2 days ago
Job description

Description :

  • Lead architecture, design, and implementation of LLM-based and agentic AI systems for clinical and operational use cases.
  • Oversee the development of multi-agent orchestration frameworks (reasoning, planning, and task execution) using tools such as LangGraph, CrewAI, or Semantic Kernel.
  • Build scalable RAG pipelines and retrieval systems using vector databases (Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
  • Guide engineers on prompt design, model evaluation, multi-step orchestration, and hallucination control.
  • Collaborate with product managers, data engineers, and designers to align AI architecture with business goals.
  • Manage end-to-end AI lifecycle data ingestion, fine-tuning, evaluation, deployment, and monitoring on Vertex AI / AWS Bedrock / Azure OpenAI.
  • Lead scrum ceremonies, sprint planning, and backlog prioritization for the AI team.
  • Work directly with external stakeholders and customer teams to understand requirements, gather feedback, and translate insights into scalable AI solutions.
  • Ensure compliance with HIPAA, PHI safety, and responsible AI governance practices.
  • Contribute to hiring, mentoring, and upskilling the AI engineering team

Must-Have Skills :

  • Deep expertise in LLMs, RAG, and Agentic AI architectures, including multi agent planning and task orchestration.
  • Hands-on experience with LangChain, LangGraph, CrewAI, or Semantic Kernel.
  • Strong proficiency in Python, cloud-native systems, and microservice-based deployments.
  • Proven track record of leading AI projects from concept to production, including performance optimization and monitoring.
  • Experience working with healthcare data models (FHIR, HL7, clinical notes) or similar regulated domains.
  • Experience leading agile / scrum teams, with strong sprint planning and delivery discipline.
  • Excellent communication and collaboration skills for customer-facing discussions, technical presentations, and cross-team coordination.
  • Deep understanding of prompt engineering, LLM evaluation, and hallucination mitigation.
  • General Skills :

  • Strong leadership, mentorship, and people management abilities.
  • Excellent written and verbal communication for both technical and non-technical audiences.
  • Ability to balance technical depth with product priorities and delivery timelines.
  • Adaptability to fast-changing AI technologies and ability to evaluate new tools pragmatically.
  • A bias toward ownership and proactive problem-solving in ambiguous situations.
  • Empathy for end-users and a commitment to responsible AI in healthcare.
  • Good to Have :

  • Experience leading AI platform initiatives or building internal AI tooling.
  • Exposure to MLOps, continuous evaluation pipelines, and observability tools for LLM systems.
  • Knowledge of multi-modal AI (text + structured + image data).
  • Prior experience integrating AI into production SaaS platforms or healthcare systems.
  • (ref : hirist.tech)

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