Director, AI Transformation

• AI transformation and adoption
• AI product/program management
• Business-process identification and optimization
• Development and deployment of AI agents/initiatives
• AI governance and guardrails
• Cross-functional coordination
• Executive communication and ownership 

What You'll Be Doing

Program Ownership and Direction
Own LaunchAI operations end to end: the workflows we target, the order we take them in, the pattern each transformation follows, and the accountability for the result.
Maintain one prioritized backlog for AI development work, sequenced by measurable business impact rather than by who asked.
Translate executive intent into an executable program of named workflows, staged capacity, and stated targets, and keep that plan current as portfolios, tooling, and priorities move.
Steward the three-tier adoption model, from individual productivity through departmental workflows to pan-Digital enterprise capability, so grassroots experimentation converts into supported capability rather than stalling.
Decide what is built, what is hardened, what is cost-optimized and democratized, and what is retired.
Workflow Transformation
Take each named workflow from measured baseline, through intervention, to measured result across all practice areas.
Direct transformation of the delivery lifecycle workflows with collaboration and integration with delivery leadership. 
Direct the cross-portfolio workflows that lift everywhere at once, including project management processes and communications, managed services triage and research, and shared IVR and web test harnesses.
Own the pan-Digital agents through pilot, beta, general availability, and the governance package that lets them scale.
AI Tooling Evaluation and Standards
Own the evaluation of AI development and productivity tooling, including agentic coding environments such as Claude Code, GitHub Copilot, and Cursor, and the platforms our agents are built on. Run structured trials against defined criteria of capability, cost, security, and fit rather than deciding on preference.
Set the standard toolset and publish what is approved, what is in trial, and what is not supported.
Manage consumption and cost across the AI toolset.
Coordinate vendor and partner relationships for AI tooling, including trials, pricing, and security.
Watch the market continuously and re-evaluate on a stated cadence.
Accountability and Measurement
Implement a baseline for every targeted workflow, covering effort, cycle time, and rework, before any intervention is built.
Publish a documented before-and-after for each workflow, quantifying the delta against that baseline.
Provide leadership reports on AI performance targets, replacing anecdotal accounts of value with measured results.
Team Leadership and Capacity
Lead developers who report into LaunchAI, setting their priorities, removing roadblocks, and protecting their capacity from the competing demands.
Define the roles, develop job descriptions, and drive hiring in partnership with portfolio and IT leadership.
Grow the LaunchAI team across partner practice portfolios.
Adoption, Communications, and Training
Work with executive leadership to secure and sustain the mandate that makes LaunchAI tooling the standard way of working, and to attach adoption KPIs to delivery leadership goals.
Treat adoption as a deliverable, converting proven solutions into delivery methodology, project templates, onboarding, and the documented way work is performed.
Run the enablement and engagement motion, including the LaunchAI Agent Hub, the AI discussion channels in Teams, the AI Zero to Hero session series, and the leaders and champions who amplify wins.
Own the LaunchAI communication plan: a steady rhythm of updates, wins, and release notes through Teams, the LaunchAI site, and leadership channels, written for a non-technical audience.
Develop and execute the training curriculum, from onboarding new employees through role-specific enablement and advanced sessions, and keep the material current as the tooling changes.
Governance, Security, and Enterprise Integration
Maintain a single channel into enterprise IT for AI work so access, environments, repositories, security review, and lifecycle are settled from day one of each build rather than retroactively.
Uphold enterprise standards for data protection, access control, environment strategy, and responsible AI across everything LaunchAI ships.
Scale and Replication
Harvest the transferable asset from the proving ground: a proven role definition, a mandate and KPI template that made adoption stick, a baseline-and-measure method leadership trusts, and shared components such as the test harness, requirements tooling, and triage.
Replicate the pattern across portfolios, adapted to each delivery model rather than copied, and contribute reusable components and evaluation approaches to a shared AI tooling library.
Feed proven delivery efficiency back into commercial models so win rate and margin reflect how the work is now performed.
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What You'll Bring to the Role

• Demonstrated experience leading enterprise AI initiatives from strategy through deployment, adoption, and measurable business outcomes.
• Experience building, deploying, or leading AI agent and generative AI initiatives within an enterprise environment.
• Strong product management mindset, with experience prioritizing initiatives and managing solutions through the full lifecycle from concept and pilot through production and scale.
• Ability to translate complex business problems and workflows into actionable AI and technology solutions, serving as a bridge between business and technical teams.
• Strong AI and technology fluency, with sufficient technical depth to effectively partner with developers, architects, IT, security, and engineering teams without requiring hands-on coding expertise.
• Proven ability to drive organizational adoption and change, including establishing adoption strategies, KPIs, enablement programs, training, and communications.
• Experience establishing measurable business outcomes for AI initiatives, including productivity gains, cycle-time improvements, cost efficiencies, adoption, and/or margin impact.
• Exceptional executive communication and presentation skills, with the ability to communicate AI strategy, recommendations, progress, and results to senior business and technology leaders.
• Demonstrated ability to lead cross-functional and technical teams, establish priorities, remove barriers, and drive accountability for results.
• Highly proactive, self-directed, and comfortable operating in ambiguity, with a proven ability to take ownership of complex initiatives with limited oversight.