Job Summary:

EnvisionWare is hiring a Director of Engineering to lead the build-out of an AI-first engineering organization. This is the most important hire in the transformation. You will own engineering execution, delivery velocity, release quality, and operational discipline across an internal engineering core and a growing Contour development pod. You report directly to the GM, and you are responsible for standing up an AI-assisted SDLC with real human gates — where AI generates more of the code, tests, and documentation, but nothing ships without your team's approval. The right person has led small engineering teams through meaningful change, has strong judgment around speed vs. quality, and is already using AI in their engineering workflow.

Job Description:

What You'll Own

Engineering execution, team performance, and production reliability across the full portfolio
The AI-first delivery pipeline: code generation, test generation, security checks, documentation, and the human approval gates that make it safe
A retained internal engineering team (3 senior engineers) and a Contour pod scaling from 1-3 to 4-6 developers based on quality proof
CI/CD ownership, deploy approval, incident response, and release discipline
The transition from sprint-heavy delivery to faster bounded bolt cycles on priority streams

How AI Changes This Role

AI generates code, tests, security scans, and documentation. Your job is to build the pipeline that makes this safe and sustainable — defining PR standards, rollback discipline, release gates, and the boundary between what AI can do autonomously and what requires human review. Speed is the goal. Losing control is the risk you manage.

What We're Looking For

10+ years of engineering leadership, ideally in environments where you built or rebuilt the engineering function
AI-assisted development experience — you've personally worked with AI coding tools and have opinions about where they work and where they don't
Experience managing or scaling outsourced/vendor engineering teams with quality standards and acceptance criteria
Comfort with Java, Angular, .NET, PostgreSQL, and Kubernetes (or strong technical breadth across similar stacks)
Strong ownership mentality — you are not a meeting-oriented manager, you are an operator who builds systems
CI/CD expertise and a track record of improving deployment frequency without increasing failure rates

What Success Looks Like (First 90 Days)

Stand up the AI-directed pipeline on pilot repos with mandatory human gates, stable rollback, and usable workflow
Define PR standards, review expectations, release ownership, and escalation paths
Reset engineering rhythm from sprints to bolt cycles on bounded streams
Ramp Contour only when quality and review load justify it — not before
Protect support, hotfix, and revenue-critical work while the new model comes online

Worker Type:

Regular

Number of Openings Available:

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