AI Implementation Lead

All Weather Insulated Panels•Vacaville, CA

10d•$130,000 - $150,000•Hybrid

About The Position

The AI Integration Program Manager is a hands-on technical owner responsible for designing, building, implementing, and scaling Artificial Intelligence, automation, and digital solutions across AWIP. The role works directly with business users, functional leaders, process owners, IT/IS, site teams, and external partners to turn approved priorities into secure, adopted, and measurable production solutions. This is not primarily a project management or vendor-coordination position. The successful candidate will personally develop, configure, prototype, test, troubleshoot, integrate, and deploy AI-powered solutions while providing the project discipline needed to move initiatives from discovery through stabilization and scale. The ideal candidate combines business acumen, technical AI expertise, solution architecture, hands-on delivery, stakeholder leadership, and change management. Success is measured by working solutions actively used by the business, reduced reliance on consultants, and sustained improvements in productivity, quality, service, decision-making, employee experience, and return on investment.

Requirements

Bachelor's degree in Information Technology, Computer Science, Engineering, Business, Operations, or a related field; equivalent relevant experience may be considered.
Five or more years of experience designing and delivering AI, automation, software, digital transformation, or enterprise technology solutions.
Proven hands-on experience developing AI agents, copilots, automations, workflows, or AI-enabled business applications.
Demonstrated ability to rapidly prototype and independently deliver technical solutions from concept through secure production deployment.
Experience integrating APIs, databases, data sources, and enterprise applications and working with internal IT/IS teams and external vendors.
Experience delivering multiple cross-functional initiatives with shared resources, interdependent workstreams, and executive stakeholders.
Experience defining KPIs, developing business cases, measuring benefits, and supporting enterprise technology adoption.
Working knowledge of Large Language Models, prompt engineering, retrieval-augmented generation, AI agents, evaluation, and related technologies.
Strong solution-design, analytical, problem-solving, technical troubleshooting, integration, and documentation skills.
Ability to balance strategic thinking, hands-on technical execution, project discipline, speed, value, risk, cost, and maintainability.
Strong stakeholder leadership and influence, including the confidence to challenge constructively and create accountability without direct authority.
Ability to turn ambiguity into practical requirements, technical options, decisions, owners, and next steps.
Excellent written, verbal, facilitation, demonstration, training, presentation, and executive communication skills.
High integrity, sound judgment, attention to detail, and ability to manage confidential information in a fast-paced, multi-site environment.

Nice To Haves

Experience with Microsoft Copilot Studio, Azure AI, OpenAI, Power Platform, Power Automate, Power Apps, and Microsoft 365.
Familiarity with Python, JavaScript, REST APIs, data integration, databases, source control, and modern development practices.
Experience with AI governance, responsible AI, cybersecurity, compliance, enterprise architecture, and solution monitoring.
Experience in manufacturing, industrial products, engineering, construction, supply chain, customer service, or corporate functions.
Experience working in a global organization and within enterprise governance structures.
AI, cloud, automation, architecture, Agile, change management, or digital transformation certification is valuable.

Responsibilities

Design, build, configure, test, deploy, and support AI-powered business solutions.
Develop AI agents, copilots, intelligent automations, workflows, chatbots, virtual assistants, and AI-enabled applications.
Create proof-of-concepts and minimum viable products to rapidly validate value, usability, feasibility, data readiness, and risk.
Translate business requirements into technical approaches, solution architecture, data needs, acceptance criteria, and implementation roadmaps.
Configure and customize AI, automation, and low-code/no-code platforms where they provide effective, maintainable solutions.
Integrate AI capabilities with approved data sources, APIs, databases, ERP, CRM, document management, reporting, and operational systems.
Use prompt engineering, retrieval-augmented generation, agent design, evaluation methods, and human review to improve solution accuracy and reliability.
Troubleshoot, optimize, document, and continuously improve deployed solutions while creating reusable standards, patterns, and components.
Own the integrated roadmap for approved AI, automation, systems, and digital transformation initiatives across functions and locations.
Evaluate and sequence opportunities using business value, strategic alignment, urgency, technical feasibility, risk, effort, dependencies, and available capacity.
Convert initiatives into practical delivery plans with scope, owners, milestones, resources, budgets, risks, decision gates, and success measures.
Take ownership from discovery and business-case validation through design, build, testing, approval, deployment, adoption, stabilization, and scale.
Manage multiple initiatives and maintain transparent status, decisions, dependencies, resource constraints, risks, and upcoming commitments.
Prevent pilots from stalling by defining ownership, exit criteria, go-live requirements, support plans, and scale decisions at the outset.
Partner directly with leaders and employees to identify repetitive, manual, information-intensive, or otherwise inefficient work.
Lead discovery sessions, design workshops, demonstrations, pilots, user testing, and feedback cycles with business and technical teams.
Translate clearly among operational, financial, and technical audiences and keep technical choices aligned with the intended business outcome.
Establish decision rights, accountable owners, working teams, communication cadence, escalation paths, and readiness expectations for each initiative.
Drive timely decisions, surface misalignment early, and communicate status and tradeoffs in concise, decision-ready terms.
Partner closely with IT/IS while representing business urgency, operational needs, security requirements, and future-state priorities.
Constructively challenge legacy assumptions or premature rejection and help teams find responsible paths to yes through alternate architecture, phased delivery, or controlled pilots.
Evaluate third-party solutions and provide build-versus-buy recommendations based on capability, integration, security, cost, scalability, support, and speed to value.
Manage vendors, consultants, and implementation partners when supplemental expertise is required, holding them accountable for quality, timelines, outcomes, and knowledge transfer.
Ensure external resources strengthen internal capability rather than replace AWIP's ownership of solution delivery.
Ensure solutions meet Kingspan and AWIP requirements for responsible AI, cybersecurity, privacy, data ownership, records management, compliance, and enterprise architecture.
Coordinate required IT/IS, Legal, Finance, HR, compliance, data, vendor, leadership, and AI Steering Group reviews early enough to protect delivery timelines.
Prepare decision-ready approval materials covering the business case, technical approach, data classification, risks, controls, readiness, and expected value.
Coordinate user acceptance testing, process changes, communications, training, job aids, go-live support, and accountable business or site champions.
Monitor adoption, proficiency, workarounds, solution performance, and operational stability until the new capability is embedded in routine work.
Define baseline performance, KPIs, and ROI assumptions with Finance and functional owners, then track realized value after deployment.
Use results and lessons learned to improve solutions, prioritization, delivery practices, and future investment decisions.