Fold Health - AI/LLM Technical Lead

Job Title: AI/LLM Technical Lead

Experience

8+ Years (AI relevant experience of 3+ years)

Location

Pune (Amar Tech Park, Balewadi) – Full-time, In-office

Domain

Healthcare (Preferred – Value-Based Care / Population Health)

About Fold Health

• Fold Health is building the
• AI foundation for value-based healthcare
• . Our in-house AI engine,

Unity

• , powers intelligent documentation, reasoning, and automation for healthcare providers, payers, and care teams.
• We’re looking for an

AI/LLM Technical Lead

• to architect, guide, and scale
• agentic and generative AI systems
• that improve care delivery efficiency and drive real-world outcomes.

Responsibilities

• 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
• .

Why Join Fold Health

• Lead the development of
• next-generation AI systems
• transforming healthcare delivery.
• Collaborate with world-class data, product, and clinical teams on meaningful challenges.

Shape the

• AI roadmap
• and mentor a growing team of engineers in an innovation-first culture.

Work on

• cutting-edge Agentic AI and LLM applications
• deployed in real-world healthcare settings.