Overview
In this role, you will act as the technical design authority for enterprise finance AI solutions, shaping scalable architectures and end-to-end delivery from early shaping to production. You’ll work across multiple pods to align with CFO agendas and senior stakeholders, turning experiments into production-ready capabilities that influence cash, profitability, and risk. You’ll thrive at the intersection of finance domain knowledge and cutting-edge AI, driving measurable business impact while staying close to technology. This is a chance to influence architecture standards and mentor engineers in a high-stakes, finance-oriented environment.
Responsibilities
- Define and maintain reference architecture for finance agents, including RAG, memory, retrieval and context engineering
- Set model routing, cost, latency, and safety requirements across proprietary/open models and cloud platforms
- Design the control plane with identity, access controls, auditability, and explainability as core architecture
- Own non-functional architecture for scalability, resilience, security, privacy, latency, and cost efficiency
- Define LLMOps and AgentOps standards, production acceptance criteria, monitoring, and incident response
- Establish secure integration patterns with ERP/EPM, data services, APIs and event-driven systems
- Provide technical authority in pursuits and client engagements from discovery through transition
- Establish engineering standards, reusable patterns, and mentoring for AI engineers
- Define measurable outcomes with finance stakeholders, focusing on quality, automation, and cost to serve
Key requirements
- Production agentic or LLM systems in enterprise at scale
- Strong architecture background: distributed systems, API/event design, cloud platforms (Azure/AWS/GCP) and data tools (DataBricks, Snowflake, Palantir)
- Hands-on depth in LLM architecture: RAG, embeddings, vector/graph retrieval, tool/function calling
- Experience with evaluation, reliability engineering, monitoring, and cost/latency optimization for LLMs
- Knowledge of responsible AI, privacy, threat modelling, GDPR/EU AI Act considerations
- Credibility with senior clients and ability to explain trade-offs to technical and finance audiences
- Ability to translate finance processes, controls and audit requirements into architecture and acceptance criteria
- At least 6 years’ relevant professional experience
- Desirable: finance ERP/EPM exposure, regulated environments, GraphRAG or knowledge-graph patterns, AI platform certifications
- Credibility with senior stakeholders
- Ability to explain trade-offs to both technical and finance leadership
- cross-functional collaboration
- LLM application architecture
- RAG and vector/graph retrieval
- tool and function calling
AI Architecture ( Manager ) in Manchester employer: Accenture
Accenture is an excellent employer for those looking to thrive in a dynamic environment, particularly in the role of Operations Engineer. With a strong focus on employee growth and development, you will have the opportunity to collaborate with senior colleagues while enjoying flexible work arrangements that promote a healthy work-life balance. The company's commitment to continuous improvement and innovation makes it a rewarding place to build your career.
