Job Description:
• Lead a distributed engineering team across platform/product engineering, connectors, QA, DevOps/infra, AI implementation, data governance, and support.
• Own delivery, quality, release discipline, and execution of the technical roadmap.
• Install engineering discipline where it's thin: automated testing, QA, CI/CD, release governance, and versioning.
• Drive repeatable, perimeter-safe deployments, including containerization, infrastructure-as-code, secure deployment, and SOC 2 readiness.
• Partner with the Chief Architect on the connector framework, canonical metadata model, architecture decisions, and product IP.
• Build the team: assess current talent, retain the strong, hire the gaps, and align the team plan to the roadmap.
• Push practical AI use across coding, review, testing, ops, and engineering productivity.
Requirements:
• Engineering leadership experience; you have run and grown teams, managed engineers, owned delivery, and shipped real product.
• Hands-on technical depth in data platforms, metadata, backend systems, or platform engineering; enough to earn the respect of strong engineers.
• Experience building or rebuilding an engineering function from the ground up, especially in a startup or early-stage environment.
• Experience installing testing, QA, CI/CD, release process, or quality practices where they did not already exist.
• Experience leading distributed or offshore engineering teams across time zones.
• Security and compliance literacy for regulated buyers, including SOC 2, audit logging, SSO, data security, or secure deployment.
• Strong AI fluency, with concrete examples of how you use AI in your own work and across engineering teams.
Benefits:
• Health insurance
• 401(k) matching
• Flexible work hours
• Paid time off
• Professional development opportunities