Senior Associate, Payroll Delivery, Newcastle Upon Tyne/Manchester/Belfast 1 1 1

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AI-Enabled Solutions Analyst

Global Payroll Operations — Technology

Grade / level

Senior Analyst / Assistant Manager (3–4 years’ professional experience)

Reports to

Business Product Manager — GPO Technology

Location

UK (hybrid), with periodic travel

Contract

Permanent, full-time

The opportunity

Global Payroll Operations (GPO) is transforming how EY delivers global payroll and tax compliance services. We are looking for an AI-enabled solutions analyst to identify operational challenges and turn them into practical, well-governed tools and improvements. You will work across the engagement lifecycle, from pursuit and pricing through delivery and close, using AI-assisted development to build and improve solutions at pace.

This is a business-facing solutions role, not a traditional software engineering position. You will use tools such as Factory.ai / Droid, Replit and other approved AI assistants to direct the creation of prototypes, data utilities, document processors and workflow automations. You will review and test the work, apply sound operational judgement, and make sure users can adopt it safely.

The principle is simple: AI helps us do more with the same. It supports practitioners and frees their time for higher-value work; it does not replace human accountability. Every output with a business or client consequence remains subject to human review.

Your key responsibilities

AI-augmented solution delivery

• Identify and build practical solutions for operational pain points across the GPO engagement lifecycle, including prototypes, data conversion utilities, document processing and automation tools.
• Use approved AI development tools to move quickly from an initial problem to a working prototype. Validate AI-generated logic and outputs, test relevant edge cases, and correct defects before sharing or release.
• Demonstrate working solutions to users early, gather feedback from Directors, Partners and engagement teams, and iterate in short cycles.
• Maintain version histories, changelogs, release notes and user-facing instructions for tools you deliver. Follow existing procedures while identifying safe opportunities to improve them.

Operational analysis and solution design

• Review processes, systems and operational data to identify inefficiencies, manual workarounds, duplicate entry, data-quality problems and control risks.
• Map processes end to end and quantify effort, error patterns and risk where evidence is available. Produce concise assessments with cited findings, severity and recommended mitigations.
• Translate user needs into clear solution requirements and acceptance checks. Challenge assumptions with evidence and keep a human accountable for decisions and exceptions.

Risk, governance and quality assurance

• Apply a client-protection mindset to each solution: sanitise data before any approved AI processing, classify outputs by confidence, route uncertain cases for human review and exclude low-confidence results rather than guess.
• Maintain an audit trail for data transformations, sanitisation, testing, decisions and releases. Map deliverables to relevant SASP controls and document rationale, limitations and rollback arrangements.
• Run structured QA before release. Record defects with severity, reproducible evidence and links to the relevant requirement or specification. Verify that data and outputs are correct, not merely present or technically generated.
• Recognise when to seek specialist advice or stop work in relation to UK GDPR, WCAG 2.2 AA, security, client confidentiality or other applicable controls.

DevOps, release and service-readiness awareness

• Use approved version-control and release processes so that changes can be reviewed, traced and reproduced. Understand the basic flow from change through build and test to deployment.
• Use available automated checks, such as tests, build validation and security scanning, as part of quality assurance; review the results and raise or resolve issues before release.
• Follow environment separation, access-control and secure-configuration practices, including approved handling of credentials and secrets. Validate a deployment, capture relevant logs or monitoring evidence, and know how to invoke the documented rollback or recovery route.

Scope of this competency: practical awareness and disciplined use of established DevOps processes. This role does not require ownership of cloud infrastructure, CI/CD platform engineering or a production operations function.

Stakeholder enablement and knowledge sharing

• Support senior, non-technical users as they adopt AI-assisted ways of working. Explain capabilities, limitations and safeguards in clear business language, without assuming a technical background.
• Create concise user guides, walkthroughs and training materials. Present and explain your approach to stakeholders, respond constructively to challenge, and adapt solutions based on feedback.
• Document reusable prompts, patterns, lessons learned and operational insights so that colleagues can benefit from them. Propose and safely test ideas that could improve the service.

Skills and attributes for success

Skills

• Demonstrable experience using AI tools to produce real work outputs, such as a prototype, analysis, document, workflow or other usable deliverable.
• Strong analytical and problem-solving skills, including the ability to investigate ambiguous operational issues, work with imperfect data and support findings with evidence.
• Ability to gather requirements, define practical acceptance checks and explain technical concepts in plain English to senior stakeholders.
• A disciplined approach to testing and quality. You review AI-generated work critically, check assumptions and edge cases, and do not treat a successful run as proof of correctness.
• Working awareness of data protection, information security, accessibility and audit requirements, with the judgement to seek advice or stop when risk is unclear.
• High-level DevOps awareness, as described above: versioning, test and release stages, secure configuration, deployment verification and rollback. Deep DevOps engineering expertise is not required.

Attributes

• Self-starting and comfortable taking ownership of loosely defined problems, forming a hypothesis, investigating the facts and presenting a practical next step.
• Curious and brave: willing to ask precise questions, challenge longstanding assumptions respectfully, demo early work and say when you do not know.
• Risk-aware and accountable, with a strong instinct to protect client data and to keep a human responsible for consequential decisions.
• Collaborative, inclusive and generous with knowledge. You take feedback constructively, explain patiently and are willing to do the practical work needed to deliver a usable solution.

To qualify for the role, you must have

• 3–4 years of professional experience in any combination of business analysis, solutions delivery, consulting, operations, software development, technology enablement, project management or product management.
• Evidence of using AI tools to create practical outputs, rather than only using them for general conversation.
• The ability to work independently through an ambiguous problem, test a proposed solution and communicate its value, limitations and risks.
• Strong written and verbal communication skills and confidence working with senior stakeholders.
• Willingness to travel periodically within the UK, in line with engagement needs.

No specific degree or formal education is required. Assessment is based on capability, relevant experience and evidence of work.

Ideally, you will also have

• Exposure to payroll, tax, financial services or professional-services operations.
• Familiarity with Python, JavaScript, HTML/CSS or another scripting language, sufficient to read AI-generated code critically and direct corrections.
• Experience with Excel, CSV, JSON, data transformation or data-quality initiatives, including messy data that does not match an expected schema.
• Basic familiarity with Azure, such as Static Web Apps, Functions or Blob Storage, or an equivalent cloud platform.
• Awareness of WCAG 2.2 AA and inclusive design principles.

What success looks like

First 90 days: Build an understanding of the GPO engagement lifecycle and its operational pain points; deliver at least one useful, AI-assisted tool or automation that has been through structured QA; work independently through a build-and-iterate cycle; and identify at least one previously unraised risk, data-quality issue or governance gap.

First 6 months: Build a portfolio of five or more documented, versioned solutions in active use; contribute evidence-based analysis to a client-facing deliverable or proposal; and enable at least two senior colleagues to use AI tools in their work.

First 12 months: Take confident ownership of a defined area of the platform or toolchain, demonstrate measurable impact, and deliver an innovation that you identified and proposed.

How we work

Our non-negotiable principles are to protect clients from risk, use AI to amplify human capability, keep a human in the loop for consequential outputs, validate AI-generated work, and maintain an audit trail for transformations, decisions and releases. No unsanitised client data enters an AI system, no unvalidated output reaches a client, and no solution is released without appropriate error handling and a documented recovery route.

We value working prototypes, honest communication, inclusive collaboration and learning through safe experimentation. We welcome neurodivergent candidates and people from non-traditional technology backgrounds. Adjustments to the application or interview process are available on request.

What working at EY offers

You will have access to enterprise AI development tools, supportive coaching and the opportunity to innovate within corporate boundaries. The role offers practical development at the intersection of business operations, technology and governance, with the flexibility to focus on outcomes and build solutions that make a measurable difference.

EY offers career development, flexible working and a competitive total rewards package. Our inclusive culture supports people to contribute in ways that work for them while delivering excellent client service.

About EY

EY brings together people, technology and services to help clients solve complex business challenges and build a better working world. Global Payroll Operations supports multinational clients across jurisdictions through payroll, tax and technology-enabled services.

If you can demonstrate the capabilities described above, we would welcome your application. Please provide your CV or professional profile and a short description (one page maximum) of what you would bring to the role. You may also share something you have built, written or created that you are proud of; it does not need to be code.

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