AI-Driven Frontline Engineer for Healthcare Ops

Habitat Health; San Francisco (CA); Hybrid; USD 181,000 - 235,000; Full time

Benefits offered by this job

Medical insurance

401(k) savings

Paid time off

Job summary

Habitat Health seeks a Forward-Deployed Engineer to design, build, and deploy AI-enabled tools such as agents, copilots, and automations across clinical, operational, and support workflows. This founding engineering hire owns data layers, integrations, prompts, and interfaces, collaborating with exec leadership to maximize value and impact.

You will ship tools from prototype to production, ensuring quality, security, and scalable deployment while driving adoption and measurable improvements in

Qualifications

• 3-6+ years of software engineering experience shipping production systems end to end in ambiguous environments.
• Experience building with modern AI tooling – agents, prompting logic, and evaluating real-world performance.
• Strong hands-on engineering across the stack and ability to establish foundations, tooling, and best practices.

Responsibilities

• Design, build, test, and ship production-grade AI tools, copilots, agents, and automations embedded in day-to-day work, owning each solution end-to-end from data layer through to interface.
• Run structured evaluations against operational expectations and debug failure modes before users.
• Maintain and improve tools in production, write documentation, and ensure reliability and usability.

Skills

AI tooling

End-to-end engineering

Architectural design

Product judgment

Data workflow design

Communication

Job description

Habitat Health seeks a Forward-Deployed Engineer to design, build, and deploy AI-enabled tools such as agents, copilots, and automations across clinical, operational, and support workflows. This founding engineering hire owns data layers, integrations, prompts, and interfaces, collaborating with exec leadership to maximize value and impact.

You will ship tools from prototype to production, ensuring quality, security, and scalable deployment while driving adoption and measurable improvements in