Vice President of Research

AI Fluency and Agentic Delivery

• Use AI development tools personally and daily, holding a current and practical command of what they can and cannot do rather than relying on secondhand reporting.
• Research and experiment continuously with new AI tooling, models, and workflows, then bring what proves out into the organization's standard practice.
• Lead every development team to agentic, human-on-the-loop delivery, where AI agents own bounded work end to end while engineers set goals, define guardrails, and review outcomes.
• Own the AI delivery-maturity roadmap across all actively supported products, applied stage by stage across the lifecycle rather than as a single global rating.
• Stand up the governance that makes delegated agent work safe, including review gates, validation, security review of AI-generated code, and measurable outcome reporting.
• Make the codebase and delivery pipeline accessible to AI agents through documentation, test coverage, CI/CD, and structured context.
• Build the tooling and training program that moves engineers from AI-assisted work, to AI-directed work, to fully delegated agent execution.
• Report AI delivery maturity and the business outcomes it produces on a recurring executive cadence.

Technical Roadmap and AI-Driven Opportunity

• Set the multi-year technical roadmap for the Corrections and Law Enforcement product lines, planned against the pace agentic delivery now makes possible rather than the timelines conventional development assumed.
• Rebuild roadmap assumptions around that acceleration. Pull committed work forward where AI-enabled delivery shortens the build, and direct the recovered capacity toward customer problems that were previously out of reach.
• Plan the roadmap around customer problems as much as product features, judging each item on whether AI can reach the outcome faster than a conventional build cycle would.
• Decide deliberately where AI belongs embedded in the products customers buy and where it is better applied as a fast path to a customer outcome, and treat both as revenue opportunities rather than internal efficiency alone.
• Balance that acceleration against customer commitments already in flight and the realities of an installed base that cannot absorb change at an unlimited rate.
• Own technology standards, architectural direction, and technical documentation across the portfolio, and hold the development organizations to them.
• Evaluate build, buy, and consolidation options where product lines overlap, and bring recommendations with supporting analysis to the Executive Vice President.
• Monitor industry direction, competitor capability, and emerging technology relevant to law enforcement, corrections, and justice software.

Delivery and Execution

• Own release commitments across every development team, including scope, sequencing, and the dates communicated to customers and to sales.
• Establish a single reporting cadence for status, blockers, and slips so that risk surfaces early rather than at the release gate.
• Standardize development process, tooling, and engineering metrics across companies that today operate independently.
• Resolve cross-team dependencies and resource contention, and escalate the trade-offs that require an executive decision.

Product Quality and Security

• Set and enforce quality standards covering code review, automated testing, defect thresholds, and release readiness, applied equally to human-written and AI-generated code.
• Maintain the highest levels of product and platform security, promoting a culture and practice of security awareness in every development team.
• Ensure development activities meet the regulatory, contractual, and industry requirements that apply to public safety and justice customers.
• Partner with Support Services to close the loop between escalated customer issues and engineering priorities.

Team Leadership and Development

• Lead, mentor, and develop the development managers and directors across the portfolio companies, setting clear goals and performance expectations.
• Recruit and retain engineering talent, and build succession depth in every key technical role.
• Set the expectation that every engineer works with AI tools as a normal part of the job, and give them the trainin