Learning Partner (AI SDLC Programme)- Edinburgh

Learning strategy and capability assessment

• Partner with CIO teams, product management, delivery leaders and the AI SDLC Coach to identify current and future capability requirements.
• Conduct learning needs analysis across different SDLC roles, personas and delivery stages.
• Translate programme priorities into an evidence-based learning roadmap.
• Develop persona capability maps and prioritised learning plans aligned with business and programme objectives.
• Apply commercial judgement when recommending learning solutions, platforms and external providers.

Learning pathway design

• Design tiered, role-specific learning pathways covering:
  • Foundational AI literacy
  • Applied AI-enabled working practices
  • Advanced AI and SDLC capabilities
• Ensure employees can access relevant learning at the point of need.
• Design inclusive, accessible and engaging learning experiences for globally distributed technology teams.
• Apply adult-learning principles and established Talent, Learning & Development standards throughout the design process.

Content creation and curation

• Create and curate high-quality learning resources using vendor content, technology platforms and internal expertise.
• Develop practical learning interventions including:
  • Realistic workplace scenarios
  • Simulations and technical labs
  • Peer-learning activities
  • Performance-support resources
  • Work-based practice
• Ensure materials meet agreed standards for accessibility, technical accuracy and responsible AI.
• Balance formal learning content with practical opportunities for employees to apply new skills.

Pilot and deployment

• Pilot learning pathways with selected technology teams before wider implementation.
• Work with managers, coaches and subject-matter experts to reinforce learning within day-to-day delivery.
• Prepare launch, communication and learner-support materials.
• Monitor participation and progression through the learning pathways.
• Identify and address barriers preventing employees from applying new skills in practice.

Measurement and evaluation

• Establish an evaluation framework that measures more than attendance and learner satisfaction.
• Track learning reach, confidence, skill progression, practical application and adoption of AI-enabled SDLC practices.
• Define baseline and post-learning measures.
• Provide clear, actionable insights to programme stakeholders.
• Use performance evidence and learner feedback to recommend targeted improvements and additional support.

Governance and continuous improvement

• Maintain the accuracy, relevance and consistency of AI SDLC learning pathways and resources.
• Keep content current as AI tools, engineering practices and governance requirements evolve.
• Apply appropriate version control, approval and content-retirement processes.
• Coordinate technical, subject-matter and governance sign-off.
• Share reusable learning practices, standards and lessons across the Change & Enablement and Talent, Learning & Development teams.
• Advise programme leaders on adult learning, capability building and behaviour change

• Strong experience in Learning & Development, learning consultancy or organisational capability development.
• Demonstrable experience managing the complete learning cycle, including:
  • Learning needs analysis
  • Learning and experience design
  • Content development and curation
  • Training delivery
  • Measurement and evaluation
• Experience partnering with technology, product, engineering or transformation teams.
• Proven ability to convert new or rapidly evolving working practices into scalable learning programmes.
• Experience designing persona-based or role-specific learning pathways.
• Strong knowledge of adult-learning principles, capability architecture and behaviour change.
• Experience creating digital learning, applied practice and performance-support solutions.
• Experience working with a combination of learning platforms, vendors and internal subject-matter experts.
• Ability to manage complex learning initiatives in fast-paced and ambiguous environments.
• Strong project planning, governance and stakeholder-management capabilities.
• Experience using learning analytics and performance evidence to assess impact and improve learning solutions.

Technical and Business Knowledge:

You do not need to be a software engineer, but you must have sufficient technical fluency to work credibly with senior technology stakeholders and globally distributed delivery teams.

An understanding of the following would be beneficial:

• Software development lifecycle practices
• AI-enabled software engineering
• Responsible AI and AI governance
• Digital learning platforms and tools
• Technology transformation programmes
• Product and agile delivery environments
• Learning analytics and capability measurement

• Excellent consultation, facilitation and coaching skills.
• Strong written and verbal communication, with the ability to explain complex subjects clearly.
• Confidence influencing senior stakeholders and constructively challenging decisions.
• Ability to create alignment across technology, programme, People and vendor teams.
• Strong analytical and problem-solving capabilities.
• Comfortable working autonomously and managing competing priorities.
• Commercially aware, pragmatic and focused on measurable outcomes.
• Able to adapt quickly as AI technologies and programme requirements evolve.
• Committed to creating accessible and inclusive learning experiences.

Qualifications:

A recognised professional qualification or accreditation in Learning & Development is desirable. Equivalent, substantial workplace experience will also be considered.