Edge Tech
AI Engineering Lead

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AI Leader
π Location: UK (Remote)
π° Compensation: Β£85,000 β Β£90,000 + up to 11% bonus
π
Contract: Permanent, Full-Time
π Visa Sponsorship: Not available. Must have the right to work in the UK without sponsorship.
π’ Reports to: Head of AI
βοΈ Split: Today, approximately 20% hands-on / 80% partner-led delivery accountability. Expected to shift toward 50/50 as the AI journey matures.
Who They Are
A major UK bank that is done talking about AI and is now building it.
This isn't a side project or a pilot programme. AI is central to how this organisation operates, with board-level sponsorship and a CEO who is an ex-Chief Digital Officer. They've already identified hundreds of automation and AI opportunities across the business. The first agentic build is going to production imminently. Claude is rolled out org-wide. Copilot agents are launching. Governance frameworks are being built from scratch. The Centre of Excellence is intentionally small - and this is your chance to join at the ground floor and shape what it becomes.
They're not looking for someone to maintain the status quo. They're looking for a technical leader who has lived and breathed AI delivery in production, can hold their own in front of a board, and is resilient enough to push through resistance in a regulated environment. If you want to build something from the ground up, with real backing and genuine influence, this is it.
Why This Role Is Special
- Greenfield opportunity: Early in the AI journey, with governance frameworks, lifecycles and controls still being built. You'll put your stamp on how this is set up.
- Board-level backing: AI has strong top-down support. You'll help explain solutions and tooling to senior leaders.
- Truly hybrid role: Not pure engineering, not pure strategy. A genuine player-coach blend of technical leadership and hands-on delivery.
- Incredible benefits: 10% matched pension, up to 11% bonus, private medical (family cover), 30 days holiday plus bank holidays, and life assurance.
- Grown-up working culture: Outcomes matter more than presenteeism. This role is fully remote.
Reasons to use Rodeo
Iβm in my final year doing Economics and I donβt know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer β it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) donβt need a masters. Letβs look at the ones youβd be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet β that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant β 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
Youβve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon β deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme β client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right β and where to focus when applying.
What You'll Own
Technical Leadership & Delivery
- Lead design and delivery of AI solutions from concept through to production, working with a primary delivery partner and other partners, contractors and academic institutions.
- Be accountable for delivery outcomes, ensuring solutions are secure, scalable, compliant and aligned to Responsible AI principles.
- Shape technical direction, standards and best practice for AI engineering across the Group.
- Work with architecture, data, technology and business teams to identify and prioritise AI opportunities.
- Define the right build, buy and partner approach for AI solutions and services.
- Provide technical leadership across cloud-based AI platforms (Azure strategic, migrating from AWS), services and integrations.
- Support the growth of AI capability and adoption across the organisation.
Hands-On Engineering
- Get hands-on with code when needed, helping to build and deploy AI, Machine Learning and Generative AI solutions in production environments.
- Work with modern AI frameworks, LLMs, RAG, prompt engineering and vector databases.
- Ensure robust MLOps practices, APIs, data pipelines and modern software engineering disciplines are in place.
Strategic & Stakeholder Engagement
- Act as a thought leader, willing to challenge the business and drive new ways of working.
- Communicate clearly and confidently to senior leaders and board level, translating complex technical concepts into business language.
- Be a resilient change agent, pushing against colleagues who have done things the same way for years.
- Help establish engineering standards, frameworks and practices that enable AI solutions to be deployed securely, responsibly and at scale.
Must-Have
- Proven Production Experience: You have "lived it, breathed it." Real commercial, production experience building and deploying AI/ML/GenAI solutions. Not just POC work or an academic pathway.
- Hybrid Technical & Strategic Skills: Deeply technical but able to present confidently to a board. The key test: "Could I put you in front of our board?"
- Strong Engineering Foundation: Excellent Python and SQL skills. Terraform and CI/CD are must-haves.
- Regulated Environment Experience: You've worked in a corporate or regulated environment (financial services, public sector, insurance, etc.) and understand corporate governance. You can "feel the pain" of red tape without being frustrated by it.
- Consultancy Background (Preferred): Experience in consultancy is a strong fit - client engagement, stakeholder presentation, and balancing technical work with strategic advice.
- Thought Leadership & Resilience: Willing to challenge the status quo and drive new ways of working, even when faced with resistance.
- UK Right to Work: No sponsorship available.


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Nice-to-Have
- Experience with Microsoft Azure, including Azure OpenAI, Azure AI Services, Azure Machine Learning and Azure Data Platform technologies.
- Knowledge of LLMs, RAG, prompt engineering, vector databases and modern AI frameworks.
- Experience with APIs, data pipelines, MLOps practices and modern software engineering disciplines.
- Experience managing partner-led delivery and a mix of onshore/offshore teams.
- Microsoft certifications (e.g., Azure AI Engineer, Azure Data Scientist).
The Process
- 30-min Initial Screen: A light chat. A chance for you to ask questions and for us to get a feel for your background and communication style.
- 1-hour Technical Interview: General technical questioning. No live coding or hackathon-style tasks. We'll explore your experience with AI/ML/GenAI, cloud platforms and modern engineering practices.
- 1-hour Functional/Competency/Values Interview: Focused on values, your ability to lead and influence, and your experience in regulated environments.
- Final Screen: A final conversation with a senior people leader for shortlisted candidates.
If you're a technically credible AI leader excited by the chance to build something from the ground up in a supportive, well-backed and genuinely flexible environment β apply now or reach out for a confidential chat.
βIt took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what Iβve been looking for.β
Jessica, London
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