The AI-Native Team Coach enables AI-Native teams to adopt, apply and continuously improve AI-Native delivery model. The role establishes effective delivery practices, develops team capability and helps teams become increasingly autonomous as they mature.
The role is accountable for improving the system through which teams deliver value by strengthening collaboration, flow, transparency, empiricism and continuous improvement. It also helps teams use approved AI capabilities to improve how they plan, build, test, coordinate and learn.
The role coaches the delivery process and ways of working. The relevant business Product role and AI Value Architect own accountability for value, product priorities, and solution direction, while the team owns delivery accountability
Responsibilities
1. Develop the AI-Native delivery model. Contribute to the design and continuous evolution of AI-Native delivery model, drawing on AI-Native SAFe, Lean, Agile, Scrum and Kanban and adapting these approaches to organisational, security and operational context.
2. Establish and evolve team ways of working. Coach teams in adopting the AI-Native delivery model, initially establishing consistent core practices and progressively enabling greater team autonomy as capability and maturity develop.
3. Strengthen empiricism and measurement. Help teams establish and use meaningful measures of outcomes, flow, quality and team health to support learning, decision-making and improvement.
4. Enable AI-supported delivery. Help teams identify activities where AI can remove repetitive work, improve quality, accelerate feedback or support better decisions, while maintaining appropriate human judgement, review, validation and accountability.
5. Address impediments and systemic constraints. Coach teams to resolve issues within their own control and facilitate broader intervention with the appropriate leaders, functions or specialists where an issue cannot reasonably be resolved within the team.
6. Build team capability and autonomy. Provide targeted coaching, facilitation and delivery interventions where they add value, while developing teams’ capability to manage their own routine planning, coordination, review and improvement activities.
7. Share learning and improve wider practice. Identify, capture and share learning across the AI-Native teams and LACE, including recurring delivery challenges, reusable practices, effective uses of AI and opportunities to improve the AINative delivery model.
Requirements
• Demonstrated experience coaching Agile teams and improving technology delivery systems in a complex enterprise environment. Experience working with small, cross-functional or highly AI-enabled teams preferred.
• Strong practical knowledge of Lean and Agile principles, Scrum, Kanban, flow, empiricism and continuous improvement.
• Experience establishing new teams or helping teams adopt, stabilise and mature new ways of working.
• Experience coaching multiple teams or working as a shared coaching capability across a portfolio, division or value stream.
• Experience helping teams visualise work and use delivery, flow, outcome, quality and team-health measures to support evidence-based improvement.
• Practical understanding of how AI tools and capabilities can augment product and technology delivery, including planning, backlog refinement, analysis, development, testing, knowledge sharing and continuous improvement.
• Strong coaching, facilitation, communication and stakeholder-engagement skills.
• Experience using Jira or comparable work-management and delivery-visualisation tools.
• Ability to recognise systemic constraints, dependencies and recurring delivery problems and facilitate appropriate cross-team or organisational intervention.
• An appropriate coaching or Agile certification, such as SAFe Practice Consultant, ICP-ACC, ICP-ATF, Certified Scrum Professional, PSM or an equivalent qualification.
Details
AI ML Engineer
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