About this opportunity
Harris Computer lists this Vice President of Research & Development opportunity in northern, Kentucky. Review the employer’s description below for duties, qualifications and application requirements.
Job description
## 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 training, access, and time to get there.* Structure the organization for the work ahead, including the balance between onshore, offshore, and contract capacity, and the reshaping that agentic delivery makes possible.* Promote transparency and collaboration by making priorities, progress, and decisions visible across the organization. ## Financial and Resource Ownership* Own the R&D budget across the portfolio, including headcount planning, capitalization, AI tooling spend, and vendor commitments.* Contribute R&D inputs to the monthly forecast and to quarterly executive reporting, with explanations for variance against plan.* Drive measurable improvement in development cost as a percentage of revenue without sacrificing delivery or quality.* Allocate engineering capacity to the products and initiatives with the strongest return, and defend those choices with data. ## Platform Modernization* Lead platform migration and modernization programs, including the sequencing and customer impact of each phase.* Retire technical debt and legacy dependencies on a published schedule rather than opportunistically, recognizing that a cleaner codebase is also a more AI-accessible one.* Measure adoption and business impact of new capability, and stop investment that does not earn its place. ## Stakeholder and Executive Communication* Act as the primary liaison between R&D and Operations, Support, Product Management, Sales, and Finance.* Present roadmap progress, AI maturity, risk, and investment recommendations to executive leadership in terms a non-technical audience can act on.* Engage directly with customers, partners, and user groups to validate direction and to hear where the products fall short.* Support due diligence and technical integration for acquisitions that join the portfolio. ## Experience and Qualifications* Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; advanced degree preferred.* Ten or more years in software development with at least three years leading engineering organizations at director level or above.* Demonstrated hands-on use of AI development tools in daily work, with a clear point of view on where they help, where they fail, and how quickly that is changing.* Experience raising an engineering organization's way of working from individual AI assistance to agentic, human-on-the-loop delivery, including the governance and validation that makes it safe.* Strong understanding of software architecture, cloud technologies, modern development methodologies, and enterprise software delivery.* A record of translating AI capability into customer-facing value and revenue, not only internal development efficiency.* Proven ownership of a multi-product or multi-company development portfolio, including budget accountability.* Experience delivering enterprise software to public sector, public safety, or other regulated markets is strongly preferred.* Track record modernizing legacy platforms while continuing to support an installed customer base.* Working command of modern architecture, cloud delivery, and secure development practice, including security review of AI-generated code.* Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent professional experience. ## Performance Measurement### Success in this role is measured on the following:* **AI delivery maturity:** Teams advancing to agentic, human-on-the-loop delivery on the published stage-by-stage plan* **Roadmap acceleration:** Committed work delivered ahead of conventional timelines, with the recovered capacity visibly redeployed* **AI-driven revenue:** Customer problems solved and revenue generated through AI capability, whether embedded in the products or applied as a fast path to an outcome* **Release predictability:** Committed releases delivered on the dates given to customers and to sales* **Product quality:** Escaped defect and escalation volume trending down release over release* **Financial performance:** R&D spend held to plan, with development cost as a percentage of revenue improving* **Organizational health:** Retention of key engineering talent and depth in every critical technical role* **Cross-functional standing:** Support, Sales, and Operations report a working, transparent relationship with R&**D****Salary range: $125,000 - $135,000 USD per year.**
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