Salary: £70,000 - 75,000 per year
Requirements
- 4 to 7 years total experience, including time at a top-tier consulting firm or AI vendor
- A track record leading end-to-end AI or data science engagements, scoping, sizing value and owning delivery through to adoption
- Enough hands-on data science / ML grounding to scope problems credibly, judge feasibility and challenge a technical team, without needing to build full time
- Strong change management and stakeholder skills, able to drive adoption across leadership and operational teams
- Commercial fluency, comfortable framing AI work in terms of business value, ROI and operational impact
- Confidence working with senior stakeholders, including in a governance-heavy environment
- Comfort operating in a lean team, going deep on content rather than just running process
- Experience across varied industries rather than a single sector is desirable
- Private equity or portfolio value creation experience is desirable
Responsibilities
- Work with business leadership to identify, size and build the case for high-impact AI use cases
- Prioritise and sequence use cases, balancing value, feasibility and organisational readiness
- Own adoption end to end, including stakeholder engagement, training and change programmes so AI tools become embedded, not shelfware
- Track outcomes against the original business case and ensure deployments translate into measurable impact
- Act as the bridge between business stakeholders and the technical build team, defining requirements and running eval/regression pipelines
- Codify what works into a repeatable playbook the wider team can reuse
Technologies
- AI
- Embedded
More
We are a financial services organisation looking for an AI Deployment Specialist to own the front end and back end of AI adoption across a live business area. You will work alongside a technical build team rather than being part of it, helping us identify and embed AI use cases that deliver measurable value. The role is not hands-on engineering, but we need someone technical enough to define requirements, run evaluation and regression checks in a low-code or no-code way, interpret results and challenge the technical approach without writing code or raising pull requests. A live example of the type of use case in scope is automating a client onboarding process that currently takes circa twenty four months to complete manually, involving document handling, data extraction, policy validation and compliance checks.
last updated 38 week of 2026
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AI Deployment Specialist - London employer: Xcede
As a Mobility Engineer/Consultant with us, you'll thrive in a dynamic remote work environment that champions innovation and collaboration. We offer competitive benefits, a strong focus on employee development, and the opportunity to work on cutting-edge enterprise solutions that make a real impact. Join our team and be part of a culture that values your expertise and encourages professional growth while ensuring you have the tools and support needed to excel in your role.
