AI Architecture ( Manager )

b Overview /b p 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. /p b Responsibilities /b ul li Define and maintain reference architecture for finance agents, including RAG, memory, retrieval and context engineering /li li Set model routing, cost, latency, and safety requirements across proprietary/open models and cloud platforms /li li Design the control plane with identity, access controls, auditability, and explainability as core architecture /li li Own non-functional architecture for scalability, resilience, security, privacy, latency, and cost efficiency /li li Define LLMOps and AgentOps standards, production acceptance criteria, monitoring, and incident response /li li Establish secure integration patterns with ERP/EPM, data services, APIs and event-driven systems /li li Provide technical authority in pursuits and client engagements from discovery through transition /li li Establish engineering standards, reusable patterns, and mentoring for AI engineers /li li Define measurable outcomes with finance stakeholders, focusing on quality, automation, and cost to serve /li /ul b Key requirements /b ul li Production agentic or LLM systems in enterprise at scale /li li Strong architecture background: distributed systems, API/event design, cloud platforms (Azure/AWS/GCP) and data tools (DataBricks, Snowflake, Palantir) /li li Hands-on depth in LLM architecture: RAG, embeddings, vector/graph retrieval, tool/function calling /li li Experience with evaluation, reliability engineering, monitoring, and cost/latency optimization for LLMs /li li Knowledge of responsible AI, privacy, threat modelling, GDPR/EU AI Act considerations /li li Credibility with senior clients and ability to explain trade-offs to technical and finance audiences /li li Ability to translate finance processes, controls and audit requirements into architecture and acceptance criteria /li li At least 6 years’ relevant professional experience /li li Desirable: finance ERP/EPM exposure, regulated environments, GraphRAG or knowledge-graph patterns, AI platform certifications /li /ul ul li Credibility with senior stakeholders /li li Ability to explain trade-offs to both technical and finance leadership /li li cross-functional collaboration /li li LLM application architecture /li li RAG and vector/graph retrieval /li li tool and function calling /li /ul