Job Title

Company overview:Join a fast-growing health-tech company that’s reimagining primary care for the modern world. As the Lead AI/ML Architect, you’ll design and build next-gen Agentic AI systems that enable clinical teams to deliver smarter, value-based healthcare. You’ll lead the architecture for multi-agent orchestration, RAG pipelines, and LLM-driven reasoning frameworks—shaping how millions experience care.The company recently raised $6 million in funding to scale its AI-first care platform, unifying providers, patients, and workflows across the U.S. healthcare system. You’ll collaborate with top engineers and data scientists to turn AI innovation into real-world healthcare impact—from automating clinical tasks to enhancing care quality and outcomes.Years of experience: 8-17 Years.Responsibilities: Lead architecture, design, and implementation of LLM-based and agentic AIsystems 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 SemanticKernel. 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 AIarchitecture 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 understandrequirements, gather feedback, and translate insights into scalable AI solutions. Ensure compliance with HIPAA, PHI safety, and responsible AI governancepractices. 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. Hands-on fine tuning of ML models (LORA, RLHF specifically) Strong proficiency in Python, cloud-native systems, and microservice-baseddeployments. Proven track record of leading AI projects from concept to production, includingperformance optimization and monitoring. Experience working with healthcare data models (FHIR, HL7, clinical notes) orsimilar regulated domains. Experience leading agile/scrum teams, with strong sprint planning and deliverydiscipline. Excellent communication and collaboration skills for customer-facing discussions,technical presentations, and cross-team coordination. Deep understanding of prompt engineering, LLM evaluation, and hallucinationmitigation.General Skills: Strong leadership, mentorship, and people management abilities. Excellent written and verbal communication for both technical and non-technicalaudiences. Ability to balance technical depth with product priorities and delivery timelines. Adaptability to fast-changing AI technologies and ability to evaluate new toolspragmatically. 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 forLLM systems. Knowledge of multi-modal AI (text + structured + image data). Prior experience integrating AI into production SaaS platforms or healthcaresystems