AI Transformation Coach

We’re looking for an inspiring, forward-looking coach with deep Agile expertise and a passion for empowering teams to unlock new possibilities through AI-driven transformation and innovation.

Mission
The Transformation Coach (AI & Agile) will be part of the Transformation team driving the evolution of our Product-Based Organization into AI-driven ways of working. The coach will work closely with Product Teams, Agile Release Trains (ARTs), and leadership to enable high-performing teams, embed AI capabilities into everyday workflows, and foster a culture of continuous innovation. This includes leveraging the company’s framework, software engineering platform, and modern AI tools and LLMs. Additionally, the coach will contribute to evolving the organization’s operating model, frameworks, develop supporting materials and execute the AI adoption plan, while actively engaging with Teams and Communities of Practice.

Key Characteristics

• Proactive, results-driven Transformation Coach with a strong Agile and AI mindset

• Hands-on approach with a proven track record transforming teams into high-performing, product-centric organizations

• Solid understanding of AI adoption in enterprise environments (e.g., GenAI, automation, data-driven decision making)

• Proven hands-on experience using AI tools (e.g., coding assistants, copilots, prompt-based tools, automation platforms) in day-to-day delivery

• Ability to coach and mentor teams, leaders, and individuals across technical and business domains

• Experience designing and facilitating workshops (Agile, Product, and AI adoption topics)

• Expertise in JIRA and Confluence; familiarity with AI-enabled productivity tools is a plus

• Excellent communication skills in English (C1+)

• Deep understanding of Agile at Scale; Lean Six Sigma and SAFe SPC certification are a plus

• Degree in IT-related field is a plus

Required Agile and AI Transformation Leadership

• Drove AI adoption initiatives, embedding AI capabilities (e.g., copilots, intelligent automation, predictive analytics) into product development and operations

• Delivered measurable improvements in productivity, time-to-market, and customer satisfaction through combined Agile and AI practices

Technical / AI Hands-on Experience

• Demonstrated hands-on experience using AI tools in the Software Development Lifecycle (e.g., GitHub Copilot, ChatGPT, Azure AI, or similar coding and productivity assistants)

• Applied AI in practical use cases such as code generation, automated testing, documentation generation, backlog refinement, and knowledge management

• Experience integrating AI tools into engineering workflows (CI/CD pipelines, DevOps processes, testing frameworks, or monitoring)

• Strong understanding of prompt engineering techniques and ability to guide teams in effective AI usage

• Familiarity with data foundations enabling AI (e.g., knowledge bases, APIs, embeddings, or model integration patterns)

• Understanding of AI governance, responsible AI practices, and enterprise constraints (security, compliance, data privacy)

Coaching and Facilitation

• Provided hands-on coaching to teams, Product Owners, and stakeholders on Agile principles and AI-enabled ways of working

• Facilitated workshops and training sessions on Agile, Product mindset, and AI literacy (e.g., prompt engineering, responsible AI usage)

• Helped teams integrate AI tools into daily workflows (planning, development, testing, and operations)

Team Collaboration and Empowerment

• Enabled teams to leverage AI to improve decision-making, reduce manual effort, and increase delivery speed

• Empowered teams to self-organize, take ownership, and continuously improve both Agile and AI practices

Continuous Improvement and Metrics

• Established and monitored KPIs across Agile delivery and AI adoption (e.g., flow metrics, cycle time, AI usage impact, productivity gains)

• Leveraged Lean, Agile, and data-driven insights to optimize workflows and identify improvement opportunities

• Encouraged experimentation and hypothesis-driven development using AI capabilities

Change Management and Culture

• Led organizational change initiatives fostering a culture of agility, innovation, and AI-first thinking

• Partnered with leadership to align business strategy with Agile and AI transformation goals

• Promoted responsible and ethical use of AI across teams, ensuring compliance and governance

Success Metrics (First 3–6 Months)

• % of product teams actively using AI tools in their daily workflows (e.g., development, testing, planning) with sustained adoption

• Measurable improvement in flow metrics (e.g., reduced cycle time, improved predictability, increased throughput)

• Number of AI-enabled use cases implemented in the SDLC (e.g., code generation, test automation, knowledge assistants)

• Adoption and standardization of AI-DLC practices across ARTs and Product Teams

• Quality improvements (e.g., reduced defects, increased automation coverage, improved release stability)

• % of teams aligned to the defined Way of Working and using standardized playbooks and practices

• Training and enablement impact (e.g., number of workshops delivered, participants upskilled, feedback scores)

• Stakeholder satisfaction (Product, Engineering, Leadership) with Agile and AI transformation progress

• Evidence of data-driven decision making through consistent usage of KPIs and insights

Impact

• Accelerate adoption of AI across product teams

• Improve productivity, quality, and innovation through AI-enabled Agile practices

• Strengthen product mindset and customer-centricity

• Contribute to a scalable, future-ready operating model

Other Details: This role offers the potential for a flexible working environment, with options for remote collaboration. The duration and industry context will be outlined during the recruitment process.