Senior AI Engineer

Responsibilities

• Build frontend interfaces, backend services, APIs, integrations, and data flows that make AI capabilities usable in patient, clinician, and internal workflows.
• Build and iterate on agentic systems that use reasoning, tool use, retrieval, memory, and multi-step workflows to solve healthcare problems.
• Build and maintain RAG pipelines, ingestion workflows, retrieval tuning, semantic search, and knowledge quality improvements.
• Implement evaluation frameworks, automated tests, experiments, regression checks, and quality metrics to improve AI system performance over time.
• Implement guardrails, fallback flows, human-in-the-loop workflows, access controls, tracing, monitoring, and diagnostics for production AI systems.
• Contribute to reliable production rollouts, CI/CD workflows, debugging, incident response, performance improvements, and operational efficiency.
• Work with senior engineers, product, clinical, design, and data partners to translate real workflows into safe, reliable AI-powered experiences.

Requirements

• 2+ years of software engineering experience, including building, testing, and maintaining production software systems.
• 1+ year of experience building with LLMs, agentic AI, or production AI systems, ideally beyond simple chatbot or prompt-only use cases.
• Strong programming skills in Python and/or TypeScript, with experience building backend services, APIs, integrations, data flows, or full-stack product features.
• Experience with modern frontend or full-stack development using technologies such as React, Next.js, TypeScript, Node.js, or similar frameworks.
• Experience contributing to AI systems involving retrieval, tool use, workflow orchestration, structured outputs, context management, or multi-step execution.
• Familiarity with agentic frameworks and orchestration tools such as LangGraph, CrewAI, OpenAI Agents SDK, or similar frameworks.
• Familiarity with RAG systems, vector databases, semantic search, retrieval infrastructure, model serving, or knowledge pipelines.
• Familiarity with cloud-native development, containerized services, Kubernetes, CI/CD workflows, or scalable production environments.
• Strong debugging, communication, and collaboration skills, with the ability to work through ambiguity and make steady progress with guidance from senior engineers.

Nice to Have

• Experience building AI systems in healthcare, clinical, safety-critical, or other regulated environments.
• Familiarity with HIPAA, clinical AI safety, FDA AI/ML guidance, or compliance-aware software development.
• Experience using tests, evaluation methods, quality metrics, experiments, observability, or release checks to improve system reliability and performance.