Lead AI Engineer

We are building an AI-powered healthcare platform that supports doctors and patients throughout their entire health journey - from first consultation to ongoing care. The platform enables intelligent conversational workflows between patients and physicians, integrated with existing portal.

• Production experience building LLM-powered applications
• Strong knowledge of RAG architectures including chunking strategies, embeddings, vector search, and retrieval pipelines
• Hands-on experience with OpenAI, Azure OpenAI, Anthropic, or similar providers
• Experience with prompt engineering, context management, guardrails, and AI output evaluation
• 5+ years of backend engineering experience
• Strong .NET / C# skills
• Experience with REST API design and implementation
• Knowledge of authentication and authorization protocols: OAuth2, OpenID Connect, JWT
• Experience with SQL and/or NoSQL databases, data modeling, and persistence layer design
• Experience with vector databases and semantic search (Azure AI Search or equivalent)
• Experience with Azure cloud platform services, deployment, and infrastructure
• Experience with containerization technologies such as Docker and Kubernetes
• Ability to independently design and own complex technical solutions
• Experience making and defending architectural decisions under real-world constraints
• Experience with production monitoring, logging, tracing, and incident management
• Strong communication skills, comfortable working with non-technical business stakeholders

AI & LLM:

• Production experience building LLM-powered applications
• Strong knowledge of RAG architectures — chunking strategies, embeddings, vector search, retrieval pipelines
• Hands-on experience with OpenAI, Azure OpenAI, Anthropic, or similar providers
• Prompt engineering, context management, guardrails, and AI output evaluation

Backend & Software Engineering:

• REST API design and implementation
• Authentication and authorization: OAuth2, OpenID Connect, JWT

Data & Infrastructure:

• SQL and/or NoSQL databases - data modeling and persistence layer design
• Vector databases and semantic search (Azure AI Search or equivalent)
• Azure cloud platform - services, deployment, infrastructure
• Containerization (Docker, Kubernetes or equivalent)

Architecture & Leadership:

• Ability to independently design and own complex technical solutions

• Experience making and defending architectural decisions under real-world constraints

• Production monitoring, logging, tracing, incident management

• Strong communication skills - comfortable working directly with non-technical business stakeholders

• Design the end-to-end architecture of the AI platform (greenfield) and integrate it with an existing patient and physician portal

• Select and implement LLM technologies and AI services appropriate for a regulated healthcare context

• Design and build RAG pipelines on curated medical knowledge sources

• Build backend services and APIs in .NET / C# to power AI workflows

• Design data storage and retrieval architecture - vector databases, structured stores, semantic search

• Implement secure authentication, authorization, and audit mechanisms

• Build conversation orchestration and physician review workflows

• Set up monitoring, evaluation, and observability for AI outputs

• Translate business and clinical requirements into technical architecture decisions

• Provide technical leadership throughout the project; optionally scale and lead a small team