AI Engineer ( Manager )

Remote Worker LTD.; Greater London; On-site; GBP 100,000 - 140,000; Full time

Job summary

Accenture is seeking a Finance AI Engineer to design, build and operate production-grade AI applications in enterprise finance environments. You will work with complex data, automate workflows and deliver secure, observable solutions that influence cash, profitability and risk.

The role emphasizes collaboration with finance users, process specialists, architects and data engineers, translating requirements into reliable software and reusable patterns across the practice.

Qualifications

• Strong software engineering discipline with Python and at least one other production language.
• Experience in version control, testing, CI, and secure coding practices.
• Experience with SQL, API design, code review and maintainable code.
• Hands-on LLM application development and MLOps concepts are a plus.
• Ability to translate finance-process requirements into testable software.

Responsibilities

• Build and deploy agentic workflows in live finance processes with clear criteria.
• Implement LLM application patterns including tool and function calling and retrieval.
• Integrate with ERP/EPM systems and secure APIs for data exchange.
• Write evaluations, instrument behavior, and ensure observability and testing.
• Create interfaces for finance users to review, approve and evidence actions.
• Package solutions using cloud AI services, containers and CI/CD pipelines.

Skills

Python

TypeScript

SQL

CI/CD

API design

Tools

Azure

AWS

Kubernetes

DataBricks

Serverless

Job description

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.

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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