Job
Description
As the Lead AI/ML Architect at this fast-growing health-tech company, you will play a crucial role in designing and building next-gen Agentic AI systems to revolutionize primary care. Your responsibilities will include: - Leading the architecture, design, and implementation of LLM-based and agentic AI systems for clinical and operational use cases. - Overseeing the development of multi-agent orchestration frameworks using tools like LangGraph, CrewAI, or Semantic Kernel. - Building scalable RAG pipelines and retrieval systems using vector databases like Pinecone, FAISS, Weaviate, Vertex AI Matching Engine. - Guiding engineers on prompt design, model evaluation, multi-step orchestration, and hallucination control. - Collaborating with product managers, data engineers, and designers to align AI architecture with business goals. - Managing the end-to-end AI lifecycle including data ingestion, fine-tuning, evaluation, deployment, and monitoring. - Leading scrum ceremonies, sprint planning, and backlog prioritization for the AI team. - Working directly with external stakeholders and customer teams to understand requirements and translate insights into scalable AI solutions. - Ensuring compliance with HIPAA, PHI safety, and responsible AI governance practices. - Contributing to hiring, mentoring, and upskilling the AI engineering team. Must-Have Skills: - Deep expertise in LLMs, RAG, and Agentic AI architectures. - Strong proficiency in Python, cloud-native systems, and microservice-based deployments. - Proven track record of leading AI projects from concept to production. - Experience working with healthcare data models or similar regulated domains. - Experience leading agile/scrum teams. - Excellent communication and collaboration skills. - Deep understanding of prompt engineering, LLM evaluation, and hallucination mitigation. General Skills: - Strong leadership, mentorship, and people management abilities. - Excellent written and verbal communication skills. - Ability to balance technical depth with product priorities. - Adaptability to fast-changing AI technologies. - A bias toward ownership and proactive problem-solving. - Empathy for end-users and a commitment to responsible AI in healthcare. Good to Have: - Experience leading AI platform initiatives. - Exposure to MLOps and observability tools for LLM systems. - Knowledge of multi-modal AI. - Prior experience integrating AI into production SaaS platforms or healthcare systems. As the Lead AI/ML Architect at this fast-growing health-tech company, you will play a crucial role in designing and building next-gen Agentic AI systems to revolutionize primary care. Your responsibilities will include: - Leading the architecture, design, and implementation of LLM-based and agentic AI systems for clinical and operational use cases. - Overseeing the development of multi-agent orchestration frameworks using tools like LangGraph, CrewAI, or Semantic Kernel. - Building scalable RAG pipelines and retrieval systems using vector databases like Pinecone, FAISS, Weaviate, Vertex AI Matching Engine. - Guiding engineers on prompt design, model evaluation, multi-step orchestration, and hallucination control. - Collaborating with product managers, data engineers, and designers to align AI architecture with business goals. - Managing the end-to-end AI lifecycle including data ingestion, fine-tuning, evaluation, deployment, and monitoring. - Leading scrum ceremonies, sprint planning, and backlog prioritization for the AI team. - Working directly with external stakeholders and customer teams to understand requirements and translate insights into scalable AI solutions. - Ensuring compliance with HIPAA, PHI safety, and responsible AI governance practices. - Contributing to hiring, mentoring, and upskilling the AI engineering team. Must-Have Skills: - Deep expertise in LLMs, RAG, and Agentic AI architectures. - Strong proficiency in Python, cloud-native systems, and microservice-based deployments. - Proven track record of leading AI projects from concept to production. - Experience working with healthcare data models or similar regulated domains. - Experience leading agile/scrum teams. - Excellent communication and collaboration skills. - Deep understanding of prompt engineering, LLM evaluation, and hallucination mitigation. General Skills: - Strong leadership, mentorship, and people management abilities. - Excellent written and verbal communication skills. - Ability to balance technical depth with product priorities. - Adaptability to fast-changing AI technologies. - A bias toward ownership and proactive problem-solving. - Empathy for end-users and a commitment to responsible AI in healthcare. Good to Have: - Experience leading AI platform initiatives. - Exposure to MLOps and observability tools for LLM systems. - Knowledge of multi-modal AI. - Prior experience integrating AI into production SaaS platforms or healthcare systems.
