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Salary: USD 139,000 - 183,000 / annual
Cityblock Health is seeking a Senior AI Software Engineer to build AI-native product features directly into their healthcare platform. You will work as a full-stack product engineer, taking AI ideas from prototype through production deployment in front of real clinical users and care teams.
Key responsibilities include implementing end-to-end feature work that integrates LLM APIs and SDKs into member- and care-team-facing product surfaces. You will own features completely: system design, model/SDK integration, evaluation frameworks, and UX design. A critical part of the role is building observability and evaluation systems alongside features to measure and continuously improve quality.
You'll embed with product, design, and clinical operations teams to identify high-value AI opportunities and translate them into shipped features. Because these features operate in a regulated healthcare environment, you'll help determine where AI acts autonomously versus where it remains advisory with human oversight, and you'll design for compliance from the start.
The role requires strong product sense—you care deeply about whether people actually use what you build and whether it delivers measurable value. You'll put prototypes in front of real users early, learn from failures, and harden the most promising concepts into production-grade features. You'll also bring honest feasibility assessments back to product and design to keep roadmaps grounded in reality.
Required qualifications: 4+ years of engineering experience with a track record of shipping full-stack product work. You need hands-on experience integrating LLM APIs or SDKs into shipped products, or closely related production experience. You should be fluent with AI assistants for engineering work and have experience building evals or quality measurement for AI features. Comfort with ambiguity and the ability to take well-scoped ideas and turn them into reality with decreasing guidance is essential. You're drawn to mission-oriented work and comfortable partnering with clinical and design experts.
Nice-to-have skills include a CS degree, prior work in regulated/compliance-heavy environments (HIPAA, SOC 2), experience building AI-native features from scratch, design prototyping ability, exposure to clinical operations, hands-on RAG experience (embeddings, vector search), familiarity with agentic patterns (tool calling, structured outputs, orchestration), and experience with LLM eval tools like Braintrust or LangSmith. Comfort with modern TypeScript/Node/React stacks, including streaming and latency-sensitive LLM UX, is valued.
