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About the role
Role Overview: As a key member of our US based Health Tech Firm, your primary responsibility will be to set the vision and build the foundational AI infrastructure. You will be instrumental in transitioning AI concepts into production-grade features that can scale effectively across thousands of patients and millions of interactions. This role requires a hands-on approach, where you will be actively involved in writing production code to drive the implementation of AI solutions. Key Responsibilities: - Architect & Execute: Take ownership of the entire AI stack, from model gateways and RAG pipelines to agent orchestration and observability. - Productionize at Scale: Design and implement systems that can move beyond prototypes, ensuring a balance between latency, cost, and safety in a high-stakes clinical environment. - AI Tool Integration: Develop a cohesive stack by utilizing LLM APIs (such as OpenAI/Anthropic), vector stores, and AI voice/telephony. - Responsible AI: Lead the development of HIPAA-compliant designs, manage PHI handling, and implement measures for hallucination mitigation. Qualifications Required: - Proven track record of successfully taking AI applications from the conceptual stage to live production environments. - Expertise in LLM concepts, including function calling, structured outputs, and streaming through modern APIs. - Hands-on experience with RAG and Agentic systems, involving embeddings, vector DBs like Pinecone/Weaviate, and multi-step tool-use workflows. - Strong skills in Python or TypeScript/JS, along with a solid foundation in backend development (REST, Async, Cloud). - Experience in building "Golden Sets" and evaluation harnesses to ensure accuracy and regression tracking. Additional Company Details: The ideal candidate for this role will possess a builder mindset, prioritizing shipping and iteration over theoretical perfection. You should also demonstrate the ability to break down complex clinical problems into simple, actionable architectures. Any experience in healthcare AI (HL7/FHIR) or regulated industries will be considered a significant advantage. Role Overview: As a key member of our US based Health Tech Firm, your primary responsibility will be to set the vision and build the foundational AI infrastructure. You will be instrumental in transitioning AI concepts into production-grade features that can scale effectively across thousands of patients and millions of interactions. This role requires a hands-on approach, where you will be actively involved in writing production code to drive the implementation of AI solutions. Key Responsibilities: - Architect & Execute: Take ownership of the entire AI stack, from model gateways and RAG pipelines to agent orchestration and observability. - Productionize at Scale: Design and implement systems that can move beyond prototypes, ensuring a balance between latency, cost, and safety in a high-stakes clinical environment. - AI Tool Integration: Develop a cohesive stack by utilizing LLM APIs (such as OpenAI/Anthropic), vector stores, and AI voice/telephony. - Responsible AI: Lead the development of HIPAA-compliant designs, manage PHI handling, and implement measures for hallucination mitigation. Qualifications Required: - Proven track record of successfully taking AI applications from the conceptual stage to live production environments. - Expertise in LLM concepts, including function calling, structured outputs, and streaming through modern APIs. - Hands-on experience with RAG and Agentic systems, involving embeddings, vector DBs like Pinecone/Weaviate, and multi-step tool-use workflows. - Strong skills in Python or TypeScript/JS, along with a solid foundation in backend development (REST, Async, Cloud). - Experience in building "Golden Sets" and evaluation harnesses to ensure accuracy and regression tracking. Additional Company Details: The ideal candidate for this role will possess a builder mindset, prioritizing shipping and iteration over theoretical perfection. You should also demonstrate the ability to break down complex clinical problems into simple, actionable architectures. Any experience in healthcare AI (HL7/FHIR) or regulated industries will be considered a significant advantage.