Senior AI Software Engineer

Overview In this role you will build and scale AI-powered features for clinical workflows, including retrieval-augmented generation and orchestrated pipelines. You contribute to model evaluation, deployment, and monitoring, ensuring HIPAA-compliant handling of health data. You participate in architecture discussions and help set engineering standards in a growing team. This position offers impact by advancing AI in healthcare and shaping production-grade AI solutions. You’ll work closely with cross-functional partners to deliver reliable, secure AI capabilities. Compensation / Benefitsmedical, dental and vision benefits 401(k) retirement savings planpaid time off and holidayspaid parental and caregiver leaveshort-term and long-term disabilitylife insurance Responsibilities Develop and maintain LLM-powered features and RAG pipelines for clinical settings Design and iterate evaluation frameworks for AI accuracy, safety, and reliability in production Build backend services in Python or Type Script exposing AI capabilities via REST, GraphQL, and Web Sockets Contribute to AI infrastructure, deployment automation, and operational tooling Ensure HIPAA-compliant development and secure handling of protected health information Engage in architecture discussions, code reviews, and establish engineering standards in a growing team Key requirements 5+ years software engineering experience with 2+ years building production AI/ML systems Hands-on experience with large language models and orchestration frameworks (Lang Chain, Llama Index, or equivalent)Proficiency in Python, Type Script, and ML libraries (Hugging Face, PyTorch, scikit-learn, or similar)Experience building REST or GraphQL APIs serving AI/ML models Strong understanding of RAG pipeline design and vector databases (Pinecone, Weaviate, pgvector, or similar)Experience building custom LLM and agent evals with automated testing of outputs and trajectories Awareness of HIPAA requirements and secure handling of health data Ability to work autonomously in a greenfield, ambiguous environment Hands-on experience with AI-assisted development tools and LLM coding harnesses (Claude Code, Pi Agent, Cursor, Codex, or similar)autonomy and strong judgmentcollaboration in architecture and design discussionsproblem-solving and proactive communicationlarge language models Lang Chain Llama Index