Senior Principal AI/ML Product Engineer (Full Stack)

Quick Facts

• Role: Sr Principal AI/ML Product Engineer (Full Stack)
• Focus: Hands-on end-to-end AI-enabled product engineering, including integrations and AI agents

Description

Build, test, deploy, evaluate, and operate production AI-enabled products end to end—from backend services and data pipelines to the interfaces care teams and patients use. Own deployment practices (infrastructure as code, CI/CD, environments, safe release practices), EHR integrations (FHIR/HL7 and vendor APIs), and AI agents/LLM features (prompt/tool design, retrieval, guardrails). Set engineering standards as a senior individual contributor: ship reliably, define “done” with evidence, and document architecture and decisions so others can run what you build.

Responsibilities

• Design, build, test, and deploy production software end to end
• Own cloud deployment practices (infrastructure as code, CI/CD, environments, release practices safe for patient care)
• Build EHR and care-system integrations including Epic, athenahealth, eClinicalWorks, and home care platforms using FHIR, HL7, and vendor APIs
• Build AI agents and LLM features across channels such as SMS and voice; implement prompt/tool design, retrieval, and guardrails
• Prototype quickly against real systems, then take working prototypes to production
• Build shared foundations with other engineering teams (integrations, deployment pipeline, evaluation harness)
• Embed evaluation into the product lifecycle: automated evaluations, behavior tests, and monitoring for drift
• Operate what you ship: instrumentation, alerting, incident response, and continuous improvement after launch
• Define “done” as proven with evidence; report what did not work promptly
• Partner with stakeholders (technology, data, security, legal, privacy, compliance, care teams) to deliver responsible, secure, enterprise-ready products
• Protect patient data by design using data minimization, access control, and audit
• Write documentation, tests, and runbooks so other teams can run the system without you
• Set engineering practices (code review, AI-assisted development, evaluation standards)
• Decide which technical decisions belong to a single market vs. the enterprise platform
• Capture weekly learnings and turn them into decisions
• Raise AI fluency of market teams via shared templates, evaluation bars, and supported ways to ship safely
• Own technical architecture and expensive-to-reverse decisions; document them

Benefits

• Comprehensive benefits package
• Incentive and recognition programs
• Equity stock purchase
• 401(k) contribution
• Salary range: $184,600–$316,500 annually (based on factors including location, education, work experience, and certifications); benefits subject to eligibility

Required Qualifications

• 10+ years of professional software engineering experience shipping and operating production systems
• Healthcare industry and/or large complex matrixed organization experience
• Full-stack experience across backend services, APIs, data stores, plus enough front-end or mobile to ship complete products
• Experience building and shipping LLM applications or agents to real users, including evaluation approach
• Ability to use AI coding/agent tools daily; built and ran an agent/automation/LLM tool
• Solid testing and operational discipline: automated tests, CI, observability, and on-call ownership
• Experience with owned cloud infrastructure and deployment: infrastructure as code, CI/CD, and enterprise security controls
• Ability to work at both enterprise and single-market levels and determine where decisions belong
• Clear technical writing skills for design decisions and findings
• Working proficiency in GitHub, AI coding/agent tools, cloud platforms, and infrastructure as code
• Senior hands-on individual contributor with end-to-end ownership
• Technical ownership experience for systems/architectures built by others

Preferred Qualifications

• Bachelor’s degree in Computer Science/Engineering or related field (or equivalent experience)
• Healthcare data integration experience (FHIR, HL7, SMART on FHIR, or Epic/athenahealth/eClinicalWorks APIs)
• Experience with HIPAA-regulated systems handling protected health information
• Experience with LLM evaluation frameworks, including building evaluation sets with domain experts
• Production experience with voice or SMS agents
• Experience taking AI capabilities through enterprise governance/review in healthcare
• Experience on small early-stage teams where engineers owned the whole stack