Feedback from the client: They are looking for someone who has acted as a hands-on Architect and is well versed in AI.
Job Title: AI Coach
Interview Location: Arlington, VA, Denver, CO, Chicago, Boston, NYC, Houston, Miami, Dallas, Minneapolis, Minn, Atlanta, GA, Birmingham, MI.
AI Coach
What the client needs: Experienced consultants to help validate whether teams are truly operating in the new AI-driven delivery model, not just self-attesting that they are. The immediate need is less about driving adoption and more about certifying/validating adoption against a defined maturity framework.
Core objective: Help assess, validate, and certify teams against the AIDLC maturity model so leadership can confidently count teams toward the broader goal of reaching 60% adoption of the “new way of working” by year-end.
Scope of Work:
• Review teams that have self-reported as operating at accelerator levels.
• Validate whether those teams are actually using AI skills, agents, plugins, and AI-driven workflows in meaningful day-to-day delivery.
• Confirm whether tools/plugins are registered in the AI catalog and aligned to the governed path.
• Assess whether team structure aligns to the intended accelerator model, such as smaller pods rather than large traditional teams.
• Pressure test and refine the certification criteria and maturity levels.
• Use data, telemetry, conversations, and delivery outcomes to support validation.
• Help define what “good” looks like for AI-enabled delivery across teams.
• Feed learnings back into enterprise guidance and operating model refinement.
Type of talent needed: This is not a traditional agile coach role. They need hands-on technical/architecture-oriented people who already understand and use AI-enabled delivery practices.
Must-have Requirements:
• Hands-on AI delivery experience.
• Strong technical or architecture background.
• Familiarity with AI-driven SDLC/AIDLC practices.
• Experience using AI coding tools, agents, skills, plugins, and workflow automation in day-to-day delivery.
• Ability to review telemetry, delivery evidence, workflows, and outcomes.
• Ability to assess whether teams are truly changing how they build and deliver.
• Comfortable operating in ambiguity and refining the framework as the work progresses.
• Able to hit the ground running with limited ramp-up time.
Nice-to-have
• Experience with AI governance, auditability, and responsible use.
• Familiarity with AI catalog/plugin ecosystems.
• Experience defining maturity models or certification frameworks.
• Experience working across enterprise teams and multiple lines of business.
• Strong facilitation skills to guide teams without coming across as punitive assessors.