openqareer

Vice President of Research & Development

Harris · Удалённо · United States · 125 000 — 135 000 USD

# Vice President of Research & Development **Harris** · United States · `Remote` · `Full Time` 💼 **Уровень роли:** `Executive` 💰 **Компенсация:** `$125,000 – $135,000` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[Vice-President]` `[Research-And-Development-Executive]` `[Director-of-Engineering]` `[Software-Development-Executive]` `[Vice-President-Of-Research-and-Development]` `[VP-Research-and-Development]` `[VP-R&D-Operations]` `[VP-Of-Research]` --- ### About the Role 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. Originally posted on Himalayas

Наблюдалась 2026-10-02, впервые 2026-10-02, источник — Himalayas (JSON API).

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