Director of Solution Delivery

Purpose of the Role: The Director of Solutions Delivery leads the agentic development team that builds rapid prototypes, refines the AI-augmented Development Lifecycle (AI-DLC), and takes successful prototypes to MVP — or hands them cleanly to IT Operations when an existing platform is the right destination. This role is the engineering engine of Digital Innovation. It partners with the Director of Digital Innovation on what to build and why, with the Director of Cybersecurity on how to build it safely, and with the Senior Director of IT Operations on how to hand off what’s built. The Director also continuously refines the AI-DLC itself — the playbook, tooling, guardrails, and engineering practices that allow a small team to deliver disproportionate output through AI-augmented development. The ideal candidate is a hands-on technologist with credible depth in modern software engineering, AI/agentic development, and rapid prototyping, and the leadership skills to grow and operate a small high-performing team.

Functional Accountabilities

1. Rapid Prototyping & MVP Development
   1. Lead the agentic development team in turning Solutions Design outputs into working prototypes, then refining the successful ones into MVPs ready for business adoption or operational handover.
   2. Maintain a delivery cadence aggressive enough to test ideas in the business quickly, and disciplined enough that the surviving ones are well-engineered.
   3. Own the criteria for advancing a prototype to MVP, retiring an idea, or routing a need to an existing platform — in partnership with the Director of Digital Innovation and the requesting business.
2. AI-DLC — The Engineering Practice
   1. Continuously refine the AI-augmented Development Lifecycle (AI-DLC): the playbook, tooling, prompts, guardrails, code-review practices, and quality gates that govern how the team builds with AI.
   2. Establish engineering standards for the team — testing, security review, secrets management, observability, and documentation — that scale across both prototypes and MVPs.
   3. Drive the productivity flywheel: each cycle of the AI-DLC should leave the team measurably faster and the work measurably higher quality.
3. Handover & Productionization
   1. Partner with the Senior Director of IT Operations on the handover of MVPs to run/scale — including documentation, operational tooling, monitoring, and the transition of accountability.
   2. Where an existing IT Operations platform is the right destination for a delivered capability, package the work for integration rather than continued ownership by Solutions Delivery.
   3. Maintain a clear inventory of what Solutions Delivery has built, where each piece lives, and who owns it post-handover.
4. Security, Safety, and Responsible AI in Development
   1. Partner with the Director of Cybersecurity to ensure every prototype and MVP is built with appropriate security and AI-safety guardrails — from secure handling of credentials and data through to the responsible deployment of agentic systems with circuit breakers and human-in-the-loop controls.
   2. Maintain the team’s practice for evaluating AI models and agent platforms, including the security and risk implications of new tools entering the development environment.
5. Vendor & Tooling Stewardship
   1. Manage the developer tooling, AI platform, and model provider relationships required for the team to operate — in coordination with the VP and the Director of Cybersecurity for the security and contractual review.
   2. Forecast and manage the Solutions Delivery operating budget, with particular attention to AI platform and model consumption costs and their ROI.

Leadership Accountabilities

• Function Leadership — Provides technical direction and operating cadence for the Solutions Delivery team. Leads by example on engineering quality, AI fluency, and craft.
• Cross-Functional Partnership — Maintains tight partnership with the Director of Digital Innovation on the design-to-build interface, with the Director of Cybersecurity on security and AI safety, and with the Senior Director of IT Operations on handover.
• Team Development — Develops the agentic development team and its hiring pipeline. Builds and maintains a team culture that prizes both speed and quality, and that treats AI as a force multiplier rather than a substitute for engineering judgment.
• Practice Evolution — Treats the AI-DLC itself as a product the team owns and improves. Maintains an explicit practice for evaluating new AI tools, models, and engineering patterns and folding the successful ones into the standard.
• Operational Excellence — Drives discipline around prototype-to-MVP advancement criteria, handover quality, and post-delivery measurement.

Core Responsibilities: General

• Lives our Values — Consistently demonstrating behaviors aligned with our Rehrig Pacific Company values and models servant leadership.
• Ensures Accountability — Drives accountability and ensures the successful execution of function key accountabilities. Proactively establishes milestones, manages dependencies, and ensures completion.
• Balances Stakeholders / Plans & Aligns — Anticipates and balances the needs of multiple stakeholders across the business. Builds and maintains healthy cross-functional relationships.
• Develops Talent — Develops people to meet both their career goals and the organization’s goals. Networks with external resources and harvests top external talent to Grow the Family. Works with team members individually as needed while promoting a healthy team environment.
• A Culture of Innovation & Belonging — Contributes to the development of our Culture of Innovation & Belonging at Rehrig Pacific, through Personnel Development (Creativity + Commitment + Courage) and Organizational Development (Diversity, Belonging, Leadership).

Qualifications:

• Bachelor’s Degree in Computer Science, Software Engineering, or a related field. A Master’s Degree would be a plus.
• A minimum of 10 years of software engineering experience, with at least 3 years leading a development team.
• Hands-on depth with modern software engineering practices, including cloud-native development, CI/CD, automated testing, and observability.
• Hands-on, current familiarity with AI-augmented development tools and agentic systems — sufficient to lead the team’s use of them by example, not theory.
• Demonstrated experience building software in a rapid prototype-to-MVP environment, with comfort retiring ideas that don’t work.
• Working understanding of security and AI safety considerations in software development.
• Strong organizational and leadership skills, with proven success in collaborative environments and outstanding communication and interpersonal abilities.
• Ability to travel approximately 15–25% of the time.