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AI Enablement Engineer; Senior

Job in San Francisco, San Francisco County, California, 94199, USA
Listing for: Sprinter Health
Full Time position
Listed on 2026-07-23
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 140000 - 210000 USD Yearly USD 140000.00 210000.00 YEAR
Job Description & How to Apply Below
Position: AI Enablement Engineer (Senior / Staff)

About Sprinter Health

At Sprinter Health, our mission is reimagining how people access care by bringing it directly to their homes. Nearly 30% of patients in the U.S. skip preventive or chronic care simply because they can’t get to a doctor’s office. For many, the ER becomes their first touchpoint with the healthcare system, driving over $300B in avoidable costs every year.

By using the same technologies that power leading marketplace and last-mile platforms, we deliver care where people are, especially those who need it most. So far, we’ve supported more than 2 million patients across 22 states, completed 130,000+ in‑home visits, and maintained a 92 NPS. Our team of clinicians, technologists, and operators has raised over $125M from investors like a16z, General Catalyst, GV, and Accel and enjoys multi-year runway.

About

the Role

We’re looking for an AI Enablement Engineer to help every team at Sprinter build, adopt, and safely scale AI‑powered workflows.

This role is about turning AI from a set of tools into a company‑wide operating advantage. You’ll work across engineering, operations, clinical, data, finance, and other teams to understand how work actually gets done, identify high‑leverage opportunities for AI, and turn those opportunities into practical systems people can use.

You’ll build bespoke agents, internal workflows, reusable templates, prompt and skill libraries, evaluation frameworks, deployment patterns, and training programs that raise AI fluency across the company. You’ll also help teams adopt AI coding assistants, agentic workflows, MCP servers, internal tools, and shared knowledge systems in ways that are useful, measurable, and safe around patient data.

This is a hands‑on builder role with a major enablement component. You should be as comfortable writing production‑quality Python or Type Script as you are running a workshop, facilitating office hours, or helping an operations lead understand how AI can improve a manual workflow.

The ideal candidate is a builder, teacher, and systems thinker who measures success by what the whole organization can now do because of the tools, patterns, and examples you created.

Office Location

We are a hybrid company based in the Bay Area with offices in both San Francisco and Menlo Park. We operate on a hybrid schedule, working from the office Monday through Thursday, with Fridays designated as work‑from‑anywhere days.

We care deeply about work‑life balance and are happy to provide flexibility when life happens. We ask that employees be in the office Monday through Thursday to collaborate with their teams while maintaining flexibility where it matters most.

Lunch is provided every day, and the entire team takes an hour to eat together. It’s one of the ways we stay connected outside of meetings. You’ll usually find us playing a board game before getting back to work.

What you will do
  • Help define and drive Sprinter’s AI enablement strategy across engineering, operations, clinical, data, finance, and other functions
  • Embed with teams to understand their workflows, identify high‑leverage AI use cases, and translate business needs into working technical solutions
  • Build bespoke agents, background workflows, internal tools, and automations that solve real operational, clinical, and engineering problems
  • Create reusable playbooks, prompt libraries, skill libraries, workflow templates, and reference architectures that teams can self‑serve
  • Stand up shared context and knowledge systems that help AI tools ground answers in Sprinter’s data, documentation, codebases, and organizational context
  • Evaluate, configure, and recommend AI tools, making practical build‑versus‑buy decisions based on team needs, safety, scalability, and cost
  • Tune AI coding assistants and agentic workflows to Sprinter’s codebases, conventions, and development practices
  • Build evaluation sets, benchmarks, and review patterns that help teams separate useful AI outputs from convincing‑but‑wrong ones
  • Establish safe, repeatable deployment patterns for AI‑built applications, internal tools, models, workflows, and data tables
  • Partner with SRE, IT, Security, Legal, and clinical stakeholders on tool approval,…
Position Requirements
10+ Years work experience
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