VP, Engineering
New
USFull-TimeVp
SalaryCompetitive base salary with performance-based bonus eligibility
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Job Details
- Experience
- 14+ years
- Required Skills
- Artificial IntelligenceRelease ManagementComplianceSoftware Engineering
Requirements
- 14+ years of combined software engineering and technical leadership experience, including significant experience leading engineering organizations at scale.
- 8+ years of experience in people leadership roles managing managers and directors.
- Demonstrated success improving engineering execution, delivery predictability, and operational rigor across multiple teams or domains.
- Experience building and evolving engineering operating models, including planning, SDLC processes, incident management, and release governance.
- Strong architectural and systems thinking, with the ability to guide modernization of complex, distributed platforms.
- Proven ability to partner effectively with executive stakeholders across product, operations, and technical functions.
- Experience working in healthcare, healthtech, or other regulated environments strongly preferred.
- Familiarity with AI-enabled engineering workflows and ability to introduce scalable, measurable AI adoption within engineering organizations.
- Excellent communication, influence, and organizational leadership skills.
- Willingness to travel and engage in periodic onsite collaboration as needed.
Responsibilities
- Lead and scale the engineering organization, including hiring, mentoring, and developing engineering managers, directors, and senior ICs to build a high-performing, mission-aligned team.
- Establish and continuously improve engineering operating systems, including planning, delivery execution, release management, incident response, and post-release learning loops.
- Drive technical strategy and architecture evolution, enabling a transition toward modern, scalable, and AI-enabled platform capabilities.
- Ensure delivery predictability and execution excellence by setting clear standards for planning, prioritization, and cross-team accountability.
- Partner with Product, Data, Clinical, Security, Legal, and Operations teams to translate business needs into executable technical roadmaps.
- Define engineering standards across quality, security, observability, compliance, and reliability while ensuring consistent application across teams.
- Lead modernization initiatives, including platform integration, interoperability improvements, and system simplification to support long-term scalability.
- Introduce and operationalize effective AI-enabled engineering practices with measurable impact on productivity, quality, and speed.
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