AI Architect – Enterprise Agentic AI Architecture
- Abu Dhabi, United Arab Emirates
نُشرت أمس
عن الوظيفة
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