AI Deployment Specialist

Xcede; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Xcede is seeking an AI Deployment Specialist to own the front end and back end of AI adoption across a live area of the business in the UK. You will identify and size AI use cases with leadership, prioritise and sequence them, and then lead change management to embed AI and deliver measurable value.

You will liaise with a technical build team while not doing hands-on coding. A live example involves automating client onboarding with data extraction, policy validation and compliance checks,

Qualifications

• 4 to 7 years' total experience, incl. top-tier consulting or AI vendor
• Track record leading end-to-end AI or data science engagements from scoping to adoption
• Hands-on data science / ML grounding to scope problems and judge feasibility
• Strong change management and stakeholder skills
• Commercial fluency with ROI and operational impact
• Comfort with senior stakeholders in governance-heavy environments
• Lean team environment focus on content over process

Responsibilities

• Identify, size and build the case for high-impact AI use cases
• Prioritise and sequence use cases, balancing value, feasibility and readiness
• Own adoption end to end, stakeholder engagement, training and change programmes
• Track outcomes against the original business case and ensure deployments deliver impact
• Bridge between business stakeholders and the technical build team, defining requirements and eval/regression pipelines
• Codify what works into a repeatable playbook for the wider team

Skills

AI/ML strategy

Stakeholder mgmt

Change management

Data science grounding

Consulting experience

Business value framing

Governance exposure

Job description

AI Deployment Specialist

My client, a financial services organisation is on the look for an AI Deployment Specialist to own the front end and back end of AI adoption across a live business area. You will identify and size AI use cases with business leadership, prioritise and sequence them, then lead the change management and adoption work needed to get them embedded and delivering measurable value.

My client, a financial services organisation is on the look for an AI Deployment Specialist to own the front end and back end of AI adoption across a live business area. You will identify and size AI use cases with business leadership, prioritise and sequence them, then lead the change management and adoption work needed to get them embedded and delivering measurable value. You will work alongside a technical build team rather than being part of it. The role is not hands‑on engineering: you need to be 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 yourself. A live example of the type of use case in scope: 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.

What you will do

• Work with business leadership to identify, size and build the case for high‑impact AI use cases


• Prioritse and sequence use cases, balancing value, feasibility and organisational readiness


• Own adoption end to end, 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

What you will bring

• 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

Desirable

• Experience across varied industries rather than a single sector


• Private equity or portfolio value creation experience