1 day ago
Manchester, United Kingdom or London, United KingdomStaff+
Responsibilities
- Define and maintain reference architectures for finance agents, including orchestration, MCP and tool design, memory, retrieval, human handoff, evaluation, rollback, model gateways, and lifecycle versioning.
- Set model selection and routing strategies across proprietary and open-weight models and cloud AI platforms, balancing cost, latency, reliability, safety, data residency, and supportability.
- Design control-plane capabilities such as segregation of duties, approval gates, evidence trails, auditability, identity and access controls, policy enforcement, and sensitive-data handling.
- Own non-functional architecture and technical assurance for scalability, resilience, security, privacy, accessibility, disaster recovery, latency, throughput, and cost efficiency.
- Define LLMOps and AgentOps standards, evaluation suites, red-teaming practices, monitoring, service levels, release management, incident response, and rollback runbooks.
- Define secure integration patterns for ERP, EPM, data and content services, workflow tools, APIs, and event-driven systems.
- Lead technical responses and architecture discussions with CFO, CIO, CTO, Chief Data and AI Officer, and enterprise architecture stakeholders.
- Establish engineering standards, reusable patterns, architecture decision records, design reviews, exception governance, and mentoring practices.
- Define measurable finance solution outcomes, including quality, automation and exception rates, control effectiveness, user adoption, and cost to serve.
Requirements
- At least 6 years of relevant professional experience.
- Production delivery experience with enterprise agentic or LLM systems at scale, including transition from proof of concept to controlled production and resolution of reliability, security, or safety incidents.
- Substantial architecture experience with distributed systems, integrations, APIs, event design, cloud platforms, identity, secrets, encryption, deployment, observability, and production operations.
- Hands-on experience with LLM application architecture, including RAG, embeddings, vector or graph retrieval, tool and function calling, structured outputs, orchestration frameworks, and model gateways.
- Experience with LLM evaluation and reliability engineering, including offline and online evaluation, groundedness, task-quality measures, failure-mode analysis, monitoring, and cost or latency optimization.
- Working knowledge of responsible AI and secure AI delivery, including threat modeling, privacy and PII controls, access control, auditability, model risk, GDPR, and EU AI Act considerations.
- Ability to explain technical trade-offs to technical leaders and finance executives and lead technical shaping in client pursuits.
- Ability to translate finance-process, control, and audit requirements into executable architecture and engineering acceptance criteria.
- Desirable experience with ERP, financial close, controls, audit, EPM, planning, finance transformation, regulated environments, semantic or knowledge-graph architectures, GraphRAG, data-product patterns, managed AI services, or relevant cloud, architecture, security, or AI platform certifications.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.