1 day ago
Manchester, United Kingdom or London, United KingdomStaff+
Responsibilities
- Define reference architectures for finance agents, including orchestration, MCP and tool design, memory, retrieval, human handoff, evaluation, rollback, RAG, graph retrieval and context engineering.
- Set model selection and routing strategies across proprietary and open-weight models and cloud AI platforms, balancing cost, latency, reliability, quality, safety, residency and supportability.
- Design control-plane capabilities such as segregation of duties, approval gates, evidence trails, auditability, identity and access controls, policy enforcement, traceability and sensitive-data handling.
- Own non-functional architecture and technical assurance for scalability, resilience, security, privacy, accessibility, latency, throughput, disaster recovery and cost efficiency.
- Define LLMOps and AgentOps standards, production acceptance criteria, evaluation suites, red-team processes, monitoring, service levels, release management, incident response and rollback procedures.
- Define secure integration patterns for ERP, EPM, data, content, workflow, API and event-driven systems.
- Lead technical shaping and responses for CFO, CIO and other senior client stakeholders from discovery through production transition.
- Establish engineering standards, reusable patterns, architecture decision records, design reviews, exception governance and mentoring practices.
- Define measurable outcomes such as quality, automation and exception rates, control effectiveness, adoption and cost to serve.
Requirements
- At least 12 years of relevant professional experience.
- Production experience delivering enterprise agentic or LLM systems at scale, including moving solutions from proof of concept into controlled production and resolving reliability, security or safety incidents.
- Substantial architecture experience with distributed systems, integrations, APIs, event design and cloud platforms such as Azure, AWS or GCP, plus production identity, secrets, encryption, deployment and observability.
- Hands-on depth in LLM application architecture, including RAG, embeddings, vector or graph retrieval, tool and function calling, structured outputs, orchestration frameworks and model gateways.
- Experience with offline and online evaluation, groundedness and task-quality measures, failure-mode analysis, monitoring, and cost or latency optimization for LLM systems.
- Working knowledge of responsible and secure AI delivery, threat modeling, privacy and PII controls, access control, auditability, model risk, GDPR and EU AI Act considerations.
- Ability to explain technical trade-offs to senior technology leaders and finance executives and lead technical shaping in pursuits.
- Ability to translate finance-process, control and audit requirements into executable architecture and engineering acceptance criteria.
- Preferred experience includes enterprise finance processes, regulated environments, semantic or knowledge-graph architectures, GraphRAG, data-product patterns, managed AI services, and 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.