Director of Engineering, Enablement and AI Tooling

Vida Health
2d$200,000 - $230,000Remote

About The Position

Vida Health is seeking a Director of Engineering Enablement & AI Tooling to build the function that makes our entire engineering organization meaningfully faster—through AI-augmented development practices, shared tooling and the core platform infrastructure that keeps everything reliable, secure and scalable. You will own how AI works at Vida as an organizational capability, not just a set of individual tools. This means building the guardrails, knowledge systems and paved-road workflows that let 25 engineers ship better code faster—while respecting the compliance and clinical data constraints that make healthcare a harder, more interesting problem than most. You will report to the VP of Engineering and work directly with engineering leads across Product, Data/AI and Clinical teams to define what AI-augmented development looks like at Vida.

Requirements

  • Bachelors Degree at a minimum.
  • 8+ years in engineering productivity, developer tooling, platform engineering or a related area—you've built things that made engineering teams measurably faster.
  • Hands-on experience with AI coding tools (Claude Code, Codex, or similar)—you understand what they're good at, where they fail and how to make them better at the org level.
  • Working knowledge of LLMs: context windows, prompting strategies and retrieval-augmented generation—you know how to structure information so AI tools use it effectively.
  • Strong Python; comfortable with CI/CD systems, infrastructure-as-code tooling and cloud infrastructure on GCP.
  • Experience in a regulated or security-heavy environment—you know how to ship with real constraints, not around them.
  • You build internal platforms engineers actually adopt—because you pair tooling with standards, training and feedback loops.

Responsibilities

  • Define and build Vida's organizational approach to AI-augmented engineering—turning individual tool usage into a shared, scalable capability.
  • Build the institutional knowledge systems that make Vida's architecture, domain context and golden path patterns accessible to both engineers and AI tools.
  • Establish technical controls and governance for AI tool usage: approved tools, PHI-safe workflows, prompt guardrails and vendor evaluation processes.
  • Own CI/CD reliability and velocity—targeting sub-5-minute median CI with automated preview environments, flake reduction and smart test selection.
  • Build paved-road developer workflows: one-command local setup, service templates, repo standards and golden path generators.
  • Own core GCP platform systems—compute, networking primitives, deployment automation and infrastructure as code.
  • Define and track the metrics that show whether enablement is working: PR cycle time, CI duration, change failure rate, time-to-first-PR for new engineers.
  • Hire and grow a team of 1–2 engineers as impact proves out.
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