Enterprise Agentic AI architecture

Role Overview

Core Requirements

• The role requires 12+ years of experience across software engineering, architecture, cloud or platform engineering, and enterprise solution delivery.
• At least 4+ years of hands-on AI engineering or AI architecture experience is required, including Generative AI, LLM applications, and Agentic AI solutions.
• Candidates must have delivered banking agents or full banking chat assistant capabilities integrated with enterprise systems.
• Strong knowledge of banking systems, retail banking journeys, payments, transfers, servicing, self-service, controls, and regulatory or security considerations is required.
• The role requires experience with Python, API integration, microservices, event-driven design, RAG, model or agent evaluation, and cloud-native deployment.
• Experience with agent frameworks, MCP servers, tool integration, interoperability protocols, cloud AI services, and secure AI system design is required.

Technical Skills

• Key skills include LLMs, prompt engineering, context engineering, memory design, tool or function calling, agent orchestration, evaluation, and cost or latency optimization.
• RAG skills include semantic indexing, embeddings, vector databases, retrieval optimization, reranking, grounding, answer relevance, and explainability patterns.
• The role uses Azure AI, Azure OpenAI, AWS AI services, Amazon Bedrock, Kubernetes, serverless, microservices, APIs, event-driven architecture, and observability.
• Security responsibilities include zero trust, PII redaction, data masking, privacy controls, guardrails, secure logging, and auditability.
• Relevant frameworks and protocols include Microsoft Semantic Kernel, AutoGen, LangChain, LangGraph, MCP, A2A, and A2UI.

Leadership and Collaboration

• The architect will define enterprise standards, influence platform direction, and simplify complex technical decisions.
• The role includes presenting architecture options, risks, trade-offs, and recommendations to senior leadership and architecture review forums.
• The position collaborates across business, product, engineering, cybersecurity, data, infrastructure, compliance, operations, and enterprise architecture teams.
• The role requires hands-on problem solving, pragmatic decision making, ownership, mentoring, and commitment to secure delivery.