Caspian One
AI Practice Transformation Lead
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Contract Length: 6-month initial contract (Then 6-month rolling)
Location: Sheffield, UK
Hybrid: 3 Days per week on-site
We are seeking an experienced, credible AI Lead for Engineering Practices (Contract Hire) to join our CTO Platforms, Engineering & Architecture team. This is a rare combination of technical depth and community influence ideal for someone who builds with AI, advocates for it with conviction and can translate that into lasting shifts in how our engineering population thinks about and applies AI in their day-to-day work.
You will define and drive the AI adoption strategy within Engineering Practices, ensuring our standards, guidance and tooling reflect the current state of the art in applied AI. You will span technical creation and community influence by building real AI capabilities while advocating internally and externally for what good AI engineering looks like. You will act as the AI conscience of the engineering community identifying where AI can unlock value, challenging where it is being used poorly and setting the bar for responsible, effective adoption.
Responsibilities
In this role, you will be required to perform the following responsibilities:
- Own the AI workstream within the Engineering Practices team, impacting AI Skills, AI Standards and AI community engagement.
- Draw from company-wide AI for Tech, AI training initiatives and AI tooling rollout to influence increasing AI aptitude within the engineering community.
- Contribute to cross-functional standards work alongside architecture, security and risk teams to ensure AI guidance is coherent and trusted across the organisation.
- Design and build AI-native interfaces that operationalise the engineering standards enabling engineers to access guidance, best practice and code patterns through AI-native interfaces.
- Serve as our internal AI developer advocate and trusted voice that engineers turn to when they want to understand how to get more from AI in their work and how to do it well.
- Build and sustain an internal AI Community of Practice by curating content, facilitating peer learning, surfacing emerging patterns and keep the community connected to the external AI engineering landscape.
- Create inspirational content for engineers including reference implementations, code samples, tutorials and playbooks that lower the barrier to responsible AI adoption for engineering teams across the bank.
- Lead on the content for internal AI engineering events, deep-dives, workshops, peer reviews and engineering showcases that inspire adoption, build capability and surface the real-world impact AI is having across the bank.
- Gather and amplify engineering voices, surface what engineers are experimenting with, what is working in production and what standards or tooling gaps need addressing.
- Produce regular insight on AI adoption trends, emerging risks and the impact of Standards & Practices work, for both engineering leadership and broader stakeholder audiences.
- Identify and document success stories where AI adoption has delivered measurable engineering outcomes and use these to drive further engagement.
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Requirements
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Essential
- Hands-on experience developing skills, plugins or integrations for AI platforms.
- A track record of building standards, patterns or best practice guidance for AI engineering that has been adopted at scale within a complex organisation.
- Demonstrable experience in leading internal and/or external AI engineering communities via conference speaking, published writing, open source contributions or community leadership that gives you credibility with engineers.
- The ability to move fluently between hands-on technical work and clear, compelling communication for engineering and leadership audiences.
- A genuine understanding of responsible AI principles, including how to design guardrails, manage non-determinism in production and apply AI at scale.
- Technical Proficiency in Python, Java and/or other programming languages and comfort across the modern AI/ML tooling ecosystem.
Desirable
- Experience working within financial services or another complex regulated environment where AI adoption requires careful governance alongside pace.
- Background in developer relations, engineering enablement or technical community building alongside engineering delivery.
- Active participation in external AI communities, with a network that keeps you genuinely ahead of the curve.
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science or related field.
- Familiarity with industry best practices for engineering maturity and provision of standards.
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