AI Architect – Enterprise Agentic AI Architecture

**JOB PURPOSE:** We are looking for an experienced AI Architect responsible for architecting enterprise\-wide Generative AI and Agentic AI capabilities across banking systems. The role will define target architecture, integration patterns, standards, reference implementations and reusable building blocks for full\-fledged AI chat assistants, autonomous agents and multi\-agent workflows. The AI Architect will lead end\-to\-end architecture for agentic retail banking journeys such as payments, transfers, servicing, self\-service fulfilment and customer assistance, ensuring secure integration with enterprise APIs, middleware, core banking platforms and customer\-facing channels across web and mobile. This role requires deep hands\-on AI engineering capability, strong banking domain understanding, practical delivery experience with multiple production\-grade banking agents, and the ability to collaborate with product, engineering, infrastructure, cybersecurity, data, governance and enterprise architecture teams to present and align designs through ARB. **QUALIFICATIONS \& EXPERIENCE:** **Minimum Qualification** * Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Technology, Artificial Intelligence, Data Science or a related discipline. * Relevant certifications in cloud architecture, AI engineering, security architecture, enterprise architecture or machine learning are preferred. **Minimum Experience** * Senior technology professional with around 12\+ years of experience across software engineering, architecture, cloud/platform engineering and enterprise solution delivery. * Minimum 4\+ years of hands\-on AI engineering or AI architecture experience, including Generative AI, LLM applications and Agentic AI solutions. * Proven experience architecting and delivering multiple banking agents or full\-fledged banking chat assistant capabilities integrated with enterprise systems. * Strong understanding of banking systems, retail banking journeys, payments, transfers, servicing, customer self\-service, operational controls and regulatory/security considerations. * Full AI Engineer capability including Python, API integration, microservices, event\-driven design, RAG implementation, model/agent evaluation and cloud\-native deployment practices. * Hands\-on experience with agent frameworks and orchestration platforms such as Microsoft Semantic Kernel, AutoGen, LangChain, LangGraph and similar frameworks. * Experience architecting MCP servers, tool integration layers, agent\-to\-agent communication, UI integration patterns and agent interoperability protocols such as MCP, A2A and A2UI. * Strong experience with Azure AI services, Azure OpenAI Service, AWS AI services, Amazon Bedrock and related model deployment/management capabilities. * Experience designing secure AI systems with zero trust principles, identity and access controls, data protection, secure API design, PII redaction and privacy\-by\-design controls. * Experience presenting solution architecture, trade\-off analysis, ADRs and architecture recommendations to ARB or equivalent architecture governance forums. * Experience recommending infrastructure architecture for AI platforms including compute, Kubernetes, serverless, vector databases, observability, monitoring, data pipelines and connectivity. * Strong capability to collaborate with engineering, product, cybersecurity, infrastructure, operations, data, compliance and enterprise architecture teams. **Key Technical Skills** * Enterprise Agentic AI architecture, multi\-agent systems, autonomous workflows, human\-in\-the\-loop design and full\-fledged chat assistant architecture. * LLMs, prompt engineering, context engineering, memory design, tool/function calling, agent orchestration, model/agent evaluation and cost/latency optimization. * RAG architecture, semantic indexing, embeddings, vector databases, retrieval optimization, reranking, grounding, answer relevancy and explainability patterns. * MCP server architecture, tool registries, multi\-tool integration, A2A, A2UI, agent interoperability protocols and AI ecosystem design. * Azure AI, Azure OpenAI, AWS AI services, Amazon Bedrock, Kubernetes, serverless, microservices, APIs, event\-driven architecture and observability. * Security architecture for AI systems including zero trust, PII redaction, data masking, privacy controls, guardrails, secure logging and auditability. **Behavioural / Leadership Skills** * Strategic architecture thinking with the ability to define enterprise standards, influence platform direction and simplify complex technical decisions. * Strong stakeholder communication with the ability to present architecture options, risks, trade\-offs and recommendations to senior leadership and ARB forums. * Collaborative leadership style with the ability to work across business, product, engineering, cybersecurity, data and infrastructure teams. * Hands\-on problem\-solving mindset, pragmatic decision making, ownership, mentoring capability and commitment to high\-quality secure delivery. **Technical Competencies** * Enterprise Agentic AI architecture and banking\-grade AI ecosystem design. * Retail banking agent architecture for payments, transfers, servicing and self\-service workflows. * RAG, memory, context engineering, evaluation, tool orchestration and MCP server architecture. * AI security architecture, zero trust, PII redaction, guardrails, auditability and governance. * Azure and AWS AI services, cloud\-native infrastructure, Kubernetes, serverless and observability for agent platforms. * Architecture documentation, ADR creation, ARB presentation and cross\-team design governance. **Skills:** AI Architecture , LLMs , Azure AI