Finance AI Engineer: Production-Grade LLM Apps

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

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.