Accenture
AI Engineer ( Manager )

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UKI Finance RP
Finance AI Engineer
The practice
Finance is one of the most demanding and valuable environments in which to apply modern technology. You will work with complex enterprise data, mission-critical processes and high-impact decisions, using AI, data and engineering to reshape how organisations plan, control performance and allocate resources. The opportunity goes beyond building technically strong solutions: you will see how those solutions influence cash, profitability, risk and business growth, and take them from experimentation into trusted, production-ready capabilities. Working in Finance Reinvention allows you to remain close to leading-edge technology while developing an understanding of the CFO agenda, gaining exposure to senior decision-makers and building the commercial judgement needed to solve enterprise-wide challenges. This combination of deep technical capability, finance-domain expertise and measurable business impact creates a differentiated career path that is difficult to develop in a purely technology-focused role.
Purpose of the role
Core build capability for the practice. Responsible for engineering agents, the orchestration around them, the evaluation harness that establishes whether they perform, and the finance user surfaces through which they are operated. The role designs, develops, tests, deploys and operates production-grade AI applications and the services around them. Embedded within a delivery pod and working on client data from an early stage of each engagement, the role translates finance-process and control requirements into secure, observable and maintainable software.
Responsibilities
- Build and deploy agentic workflows into live finance processes, including reconciliations, journals, exception handling, disputes, collections and variance explanation, with clear acceptance criteria, human oversight and controlled failure behaviour.
- Implement LLM application patterns including tool and function calling, structured outputs, RAG or graph-based retrieval, context and memory management, multi-agent orchestration, and prompt or configuration versioning.
- Integrate with ERP and EPM systems, document repositories and workflow tooling, including the data extraction, transformation and error handling that integration requires, using secure APIs, events, identity controls and reusable connectors where appropriate.
- Write evaluations, instrument agent behaviour, and ensure failure modes are visible and recoverable, using automated functional and non-functional tests, trace-level observability, red-team scenarios and measures for quality, groundedness, latency and cost.
- Build the interfaces through which finance users review, approve, override and evidence agent actions, including provenance, citations, feedback capture, accessibility and clear error-recovery journeys.
- Package and operate solutions using cloud AI services, containers or serverless components, CI/CD, infrastructure as code, secrets and configuration management, monitoring, release controls and rollback.
- Work directly with finance users, process specialists, architects and data engineers to clarify requirements, challenge assumptions constructively, demonstrate increments and document operating procedures and runbooks.
- Contribute reusable patterns and components back to the practice asset base, including tested code, evaluation assets, reference implementations and implementation guidance.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d 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 — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 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
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — 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 — 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 — and where to focus when applying.
Essential experience
- Strong software engineering discipline, including Python and at least one additional production language such as TypeScript or equivalent, version control, testing, CI, and maintainable code, together with SQL, API design, code review and secure coding practices.
- Hands-on LLM application development, covering tool use, structured outputs, retrieval and agent frameworks, including embeddings, vector or graph retrieval, prompt and configuration management, and integration with enterprise data or services.
- Practical experience with evaluation, observability and LLMOps or AgentOps, including versioning, monitoring, release and rollback, and analysis of quality, latency and cost.
- Understanding of secure enterprise integration and sensitive-data handling, including authentication, authorisation, secrets, logging and PII-aware design.
- Ability to work client-side and collaborate effectively with non-technical finance users, translating their needs into testable requirements while explaining options, risks and trade-offs clearly.
- At least 6 years’ relevant professional experience
Desirable
- Front-end capability alongside back-end, sufficient to deliver a usable interface independently, for example React, Next.js or an equivalent framework.
- Prior exposure to SAP, Oracle, Workday, Anaplan or OneStream, or to finance processes such as close, planning, order to cash or procure to pay.
- Experience with MCP, graph or semantic retrieval, data engineering, event-driven integration or workflow orchestration.
- Experience deploying software or data products on Azure, AWS or GCP, DataBricks, Snowflake, Palantir etc. using relevant cloud services and at least one of containers, Kubernetes or serverless patterns.
- Delivery experience in a regulated environment or under formal responsible-AI, security or model-risk controls.


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About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.
Visit us at www.accenture.com
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