Director of Platform Engineering, Doma

• 7+ years of experience in infrastructure, platform, or DevOps engineering, including hands-on experience on Azure, Kubernetes, Postgres and data warehousing
• 3+ years managing engineers or engineering managers
• Deep experience with CI/CD, GitOps, and infrastructure as code
• Demonstrated proficiency directing AI coding and infrastructure tools to deliver production systems. You can architect the outcome, prompt and steer the AI effectively, and critically review what it produces — you treat AI as a force multiplier while remaining fully accountable for the quality, security, and correctness of the result
• Experience owning secrets management and related tooling
• Comfort operating databases and data warehouse infrastructure at scale
• A track record of staying hands-on: writing code, reviewing architecture, and working incidents alongside your team, not just directing from above
• Strong communication skills, comfortable explaining technical tradeoffs and risk to non-technical stakeholders

Desirable

• Doma is looking for a hands-on Director of Platform Engineering to own the infrastructure and DevOps foundation our product, software, and data teams build on
• At Doma, we build differently. The platform supporting our environment was designed and stood up through human-directed AI
• This role owns and extends that estate, so fluency in directing AI tools to produce production-grade, secure infrastructure is essential
• You will report to our VP Engineering and will be expected to both set direction and stay close enough to the systems yourself to review architecture, work through incidents, and do part of the build alongside your team. This is a backfill at the Director level, with a scope intentionally focused on infrastructure and DevOps
• Own our cloud infrastructure (Azure) and Kubernetes environment, keeping it reliable, secure, and cost efficient
• Lead the team in using AI-assisted engineering to design, build, and operate platform infrastructure — setting the standards, guardrails, and review practices that make AI-generated code and infrastructure reliable, secure, and maintainable at scale
• Drive infrastructure as code, CI/CD, and GitOps practices that let engineering teams ship safely and quickly
• Own secrets management and the DevOps tooling that underpins our deployment pipeline
• Maintain and evolve our database and data warehouse infrastructure
• Build observability and reliability practices, and improve developer experience across engineering
• Manage and mentor a team of engineers and engineering managers, while staying hands-on enough to contribute directly to the work
• Partner with Security and Corporate IT on any handoffs between platform and security