AI Enablement Engineer (Senior / Staff)
About The Position
Sprinter Health is seeking an AI Enablement Engineer to help all teams within the company build, adopt, and safely scale AI-powered workflows. This role is crucial for transforming AI from a set of tools into a company-wide operating advantage. The engineer will collaborate across various departments, including engineering, operations, clinical, data, and finance, to understand existing workflows, identify high-impact AI opportunities, and develop practical systems for widespread use. Key responsibilities include building bespoke agents, internal workflows, reusable templates, prompt and skill libraries, evaluation frameworks, deployment patterns, and training programs to enhance AI fluency across the organization. The role also involves assisting teams in adopting AI coding assistants, agentic workflows, MCP servers, internal tools, and shared knowledge systems, ensuring their usefulness, measurability, and safety, particularly concerning patient data. This is a hands-on position requiring both strong software development skills (Python, TypeScript) and the ability to teach and facilitate, such as running workshops or office hours. The ideal candidate is a builder, teacher, and systems thinker who prioritizes organizational enablement and measurable impact.
Requirements
- Built production-quality software in Python, TypeScript, or similar languages
- Worked hands-on with LLMs, AI assistants, agents, tool calling, structured outputs, RAG, or other applied AI patterns
- Built internal tools, automations, workflows, developer productivity tooling, AI-enabled applications, or agentic systems
- Designed practical evaluations, benchmarks, or QA processes for AI workflows or software systems
- Worked with CI/CD, testing, deployment pipelines, or production release processes
- Gathered requirements from non-technical stakeholders and translated them into scoped, working technical solutions
- Enabled teams through documentation, training, office hours, workshops, hackathons, or reusable templates
- Used AI coding assistants such as Claude Code, Cursor, or similar tools as part of your day-to-day development workflow
- Made practical tradeoffs between speed, safety, usability, maintainability, and cost
- Communicated technical concepts clearly to audiences ranging from engineers to executives
- Operated in fast-moving, ambiguous environments where the path was not already defined
Nice To Haves
- Operated at Senior, Staff, or equivalent scope, driving technical decisions across multiple teams
- Built internal AI platforms, agent frameworks, evaluation systems, workflow automation platforms, or developer productivity tooling
- Helped a company or team adopt AI tools in a measurable, repeatable way
- Experience standing up a centralized prompt library, skill library, workflow library, or knowledge/context hub
- Worked with MCP servers, internal tool integrations, RAG systems, or AI agents connected to real business systems
- Experience with healthcare data, PHI, HIPAA-aware workflows, or regulated environments
- Partnered with security, IT, legal, compliance, or clinical teams to approve and deploy AI tools safely
- Public or internal track record of teaching, writing, workshops, talks, or training that made complex technical ideas accessible
- Worked in a startup or high-growth environment where enablement, velocity, and practical judgment mattered
Responsibilities
- 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, deployment, access patterns, and PHI-safe guardrails
- Run recurring office hours, trainings, hackathons, and hands-on enablement sessions that build AI fluency across the company
- Measure AI adoption, productivity gains, quality improvements, and operational impact in ways that go beyond usage or token counts
- Communicate AI strategy, adoption progress, risks, and opportunities to individual contributors, managers, and executive leadership
- Help non-experts move quickly while ensuring patient safety, privacy, and quality are built into the workflow from the start
Benefits
- Meaningful pre-IPO equity
- Medical, dental, and vision plans 100% paid for you and your dependents
- Flexible PTO + 10 paid holidays per year
- 401(k) with match
- 16-week parental leave policy for birthing parent, 8 weeks for all other parents
- HSA + FSA contributions
- Life insurance, plus short and long-term disability coverage
- Free daily lunch in-office
- Annual learning stipend
- Relocation assistance
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
