VP of Engineering

Key Responsibilities

• Lead a unified, multi-disciplinary engineering organization focused on operational excellence and a culture of high accountability.
• Partner with product leadership to align technical capacity with product prioritization, creating a reliable, transparent, and repeatable release cadence.
• Direct major enterprise initiatives, including the systematic modernization of the legacy codebase and the integration of AI-assisted tools into daily workflows.
• Achieve and maintain a high sprint and release commitment success rate of greater than 85 percent within the first six months.
• Drive the successful adoption of AI-assisted tooling across engineering and quality assurance teams to achieve a 20 to 30 percent reduction in standard cycle times.
• Deliver a comprehensive codebase refactoring and migration blueprint within 90 days, executing Phase 1 milestones by month nine.
• Transition the quality assurance framework from manual testing to an automated, AI-augmented model that reduces post-release defect escapes by 25 percent.
• Optimize capacity allocation to achieve a target distribution of 60 percent innovation, 20 percent legacy modernization, and less than 20 percent ongoing maintenance by month six.

Requirements

• 10 or more years of progressive software engineering experience, including 4 or more years in a senior engineering leadership role with direct ownership of multiple functions.
• Proven track record leading and scaling engineering organizations in a B2B SaaS company through significant growth or transformation phases.
• Experience partnering at the executive level to translate technical strategy into business outcomes and align investment decisions to company-level growth objectives.
• Experience owning and managing an engineering P&L, including budget planning, headcount allocation, vendor spend, and cloud infrastructure costs.
• Proven experience leading large-scale legacy modernization efforts, architectural refactoring, and service decoupling while maintaining product delivery continuity.
• Hands-on experience with AI-assisted development tooling and a track record of driving adoption and measurable productivity gains across an organization.
• Experience implementing CI/CD pipelines, automated QA frameworks, and metrics programs to drive engineering delivery predictability and quality.
• Exceptional strategic capability, change leadership skills, and a resourcefulness that establishes a strong bias for action across teams.

Skills and Knowledge

• Familiarity with compliance, legal, or regulated industry software where data accuracy and auditability are core requirements.
• Experience navigating rapid organizational scaling or post-acquisition integration within a private equity-backed environment.
• Deep knowledge of engineering metrics frameworks, such as DORA metrics, cycle time analysis, and defect escape rates.
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical discipline.