Senior Software Engineer

Cityblock Health

14d•$110,000 - $145,000

About The Position

Cityblock is seeking a full-stack product engineer to bring AI-native ideas from early prototypes into production features used by clinical teams and members. The role focuses on shortening the distance between an idea and a useful product, then making effective AI features dependable within a regulated healthcare environment. Reporting to the Product Engineering organization, the engineer will own end-to-end feature development, including system design, LLM and SDK integration, evaluations and golden datasets, and user experience. The role partners with product, design, clinical operations, and the data organization. It also helps determine when AI should act autonomously versus remain advisory with a human in the loop, and how to demonstrate that features are safe and trustworthy while designing for compliance from the outset.

Requirements

At least 4 years of experience as an engineer.
Strong full-stack product engineering ability and a track record of shipping working software.
Experience integrating LLM APIs or SDKs into a shipped product, or closely related production experience that can be built on.
Strong product sense and concern for product adoption and measurable value.
Comfort with ambiguity and ability to turn a well-scoped, high-value idea into a real product with decreasing guidance over time.
Experience building evaluations or quality measurement for AI features, or a clear instinct that these are needed.
Fluent daily use of AI assistants for engineering, with sound judgment about when to trust them.
Interest in mission-oriented work and comfort partnering with clinical and design experts.

Nice To Haves

A computer science degree or equivalent.
Prior experience in a regulated or compliance-heavy environment, such as HIPAA or SOC 2.
Experience building AI-native product features from scratch, including their evaluations.
Design sensibility sufficient to prototype user experiences independently.
Exposure to clinical operations or experience working alongside clinical staff as end users.
Hands-on experience with retrieval-augmented generation, including embeddings, vector search, and grounding LLM output in trusted context.
Familiarity with agentic patterns, including tool or function calling, structured outputs, and multi-step orchestration.
Experience with LLM evaluation and observability tools such as Braintrust or LangSmith, and LLM-as-judge techniques.
Comfort with a modern TypeScript, Node, and React stack, including streaming and latency-sensitive LLM user experiences.

Responsibilities

Implement full-stack features integrating LLM APIs and SDKs into products used by members and care teams.
Own features end to end, including system design, model and SDK integration, evaluations, and user experience.
Build observability and evaluations alongside features so quality can be measured and improved.
Apply and help improve the team's prototyping loop, evaluation discipline, and quality bar through shipped work.
Put prototypes in front of real users early, learn from what breaks, and harden promising prototypes for production.
Provide product and design teams with an honest assessment of what is feasible so roadmaps reflect reality.
Work with product management, design, and clinical operations to identify and understand valuable AI opportunities.
Partner with the data organization to obtain grounded, trustworthy context for features.