Senior AI Adoption Evangelist

Roles and Responsibilities :

Own the Enablement Flywheel

Run Enable Adopt Measure Improve as one continuous loop, so gains compound with every model release instead of decaying after the initial

rollout.

Take direct ownership of a capability area that today is spread thin across ~6.1 FTE and 25 initiatives, with no single accountable owner.

Scale the Champions Network

Grow JedAI from a ~0.7 FTE operation into a resourced, multi-site cascade — Champions are opt-in volunteers, seeded from teams with a live

codebase, a keen engineer, and a willing lead, not draftees.

Design a tiered curriculum (equivalent to a 201 “build faster” track for fluent teams and a 202 “build skills” track for the broader cohort) on top of

the existing Video Content Program and Learning Path.

Keep pace with the tools through a standing power-user curriculum and regular office hours, so the programme doesn't go stale between model

releases.

Build the Readiness & Efficiency Measurement Layers

Readiness: extend the existing Claude Code Security Assessment and AI Golden Rules into a full, deterministic repo-readiness audit —

standards, guardrails, architecture, and test quality — run entirely inside Worldline's own environment.

Efficiency: stand up the telemetry layer Worldline doesn't have today — token economy, cache-hit rates, model mix — so cost and practice are

tuned as adoption scales, not audited after the fact.

Drive Business Impact & ROI Reporting

Push AURA / Statistics Dashboard's Developer Friction Score toward a formal before/after methodology — cycle time, review time, and

throughput on the same repositories, expressed in the currency the business already tracks.

Report business impact on Worldline's own dashboards on a regular cadence — no duplicate tooling, no external dependency for a core

capability.

Codify Advanced Practice

Turn the MCP servers already connecting Jira, Confluence, and GitLab into a governed, shared “ticket-to-merge-request” template — today's

plumbing becomes tomorrow's default workflow.

Own the AI Marketplace's governance question: build the shared, guardrailed skills library so a correction one engineer makes becomes a

preference the next team inherits, rather than staying in one person's head.

Partner Across the Engineering Excellence Portfolio

You will collaborate closely with Product Owners responsible for:

Developer Platform & Experience — internal developer platform, CI/CD, self-service capabilities.

Quality & Automation — test automation, release automation, delivery quality metrics.

Security Engineering & Enablement — secure-by-design practices, shift-left security, developer security tooling.

Tech Enablement & AI-Powered Engineering — the home team for AI-assisted development capabilities, Claude Code, GitHub Copilot, andemerging platforms.

Job Requirements :

• 3–5+ years in developer enablement, platform engineering, technical training, or a hands-on senior/staff engineering role with a strong coaching

  track record.

  Hands-on fluency with Claude Code, GitHub Copilot, or comparable AI-assisted development tools — you use them daily, not just advocate for

  them.

  Working knowledge of MCP-based tooling, RAG/codebase indexing, and agentic workflows, or a fast track record of picking up new AI tooling

  paradigms.

  Strong analytical mindset — comfortable defining adoption/productivity KPIs and building the before/after case that survives a finance review.

  Experience running or scaling a champions / communities-of-practice model across distributed, multi-site teams.

  Excellent facilitation and stakeholder management skills — able to influence Product Owners, security, and engineering leadership without formal

  authority.

  Fluent in English.

  Your Soft Skills & Personal Attributes

  Engineer-obsessed: you treat the ~2,500 engineers you're enabling as your primary customer.

  Data-driven and outcome-oriented — allergic to “hours-saved” claims that don't survive scrutiny.

  Genuinely curious about emerging AI capabilities, and quick to separate signal from hype.

  A natural teacher — you'd rather build ten Champions than be the only expert in the room.

  Comfortable holding a programme accountable to a hard gate (a 90-day-style reassessment) rather than a vague sense of progress.

  Balances strategic ownership of the flywheel with the pragmatism to ship the next Champion cohort this quarter.

  Nice to Have

  Experience building or specifying developer-productivity dashboards or engineering performance indicators.

  Familiarity with FinOps practices and AI/cloud cost optimization (token economy, model mix tuning).

  Background in security engineering or compliance-adjacent enablement (PCI-DSS, ISO-27k).

  Prior experience evaluating or managing an external enablement partner (e.g. a vendor-delivered coaching engagement) alongside an internal build.