Establish responsible AI usage guidelines and guardrails
Deploy AI tools and workflow redesign that measurably improves throughput, quality, and cost
Lead cross-functional change management to drive real adoption—from executives to individual developers and delivery teams
Create and maintain a 6-12–24 month AI roadmap across engineering, delivery, and business operations, with clear milestones and measurable outcomes.
Establish an ROI model and prioritize initiatives using value, feasibility, risk, and time-to-impact.
Assess current product development workflows and identify high-leverage AI opportunities.
Deploy and operationalize AI-assisted development practices: AI pair-programming, code review augmentation, unit/integration test generation support Refactoring assistance, documentation generation, dependency mapping and impact analysis
Define quality gates and governance so AI accelerates delivery without increasing defect risk.
Improve delivery metrics (cycle time, rework, escaped defects, utilization, on-time milestones) through automation and better information flow.
Requirements
10+ years of progressive experience spanning technology leadership, digital transformation, or engineering productivity
Experience implementing AI in public sector and/or highly regulated environments
Proven experience implementing AI/automation initiatives that delivered measurable ROI (not just prototypes).
Strong fluency in modern software development lifecycles; ability to work credibly with developers and architects.
Demonstrated ability to design and operationalize governance/guardrails for AI use, including data risk management.
Exceptional executive communication skills with the ability to translate technical concepts into business outcomes.
Track record of leading cross-functional change initiatives: adoption, training, and sustained process improvement.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent experience required.
Advanced degree (MBA, MSCS, or related) is a plus.