Role Purpose

Define and govern Mashreq s enterprise AI architecture across the AI CoE, Agentic AI Ecosystem, Enterprise AI Platform, and Trade Virtual Assistant initiatives. The role establishes target-state architecture, secure reusable patterns, platform and integration standards, and technology roadmaps that align AI investment with Mashreq s AI Strategy, enterprise architecture, risk appetite, and digital transformation goals.

Key Responsibilities

Strategic Responsibilities

- Own the current-state, target-state, transition, and reference architectures for AI, GenAI, RAG, AI agents, and multi-agent ecosystems.

- Define platform strategy, capability roadmaps, architectural principles, approved patterns, and technology selection criteria.

- Shape adoption of LLMs, prompt engineering, MCP, tool calling, function calling, orchestration, model hosting, and grounding patterns.

- Drive reuse, interoperability, scalability, resilience, portability, cost efficiency, and avoidance of fragmented AI solutions.

Delivery Responsibilities

- Translate business capabilities and non-functional requirements into solution architecture, integration designs, and implementation guardrails.

- Architect Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric solutions.

- Review solution designs, proof-of-concepts, vendor proposals, APIs, data flows, deployment models, MLOps, observability, and disaster-recovery approaches.

- Guide engineering teams through design decisions, technical risks, performance constraints, and production readiness.

Governance Responsibilities

- Establish architecture governance for Responsible AI, security, privacy, compliance, model risk, data residency, auditability, and lifecycle controls.

- Maintain architecture decisions, standards, patterns, exception records, risk treatments,



and technical debt roadmaps.

- Ensure alignment with enterprise architecture, cybersecurity, data governance, cloud, integration, and operational resilience standards.

Stakeholder Management Responsibilities

- Advise the Head of AI, Enterprise Architecture, Technology leadership, business executives, Risk, Compliance, Information Security, and governance forums.

- Lead architecture workshops and vendor evaluations; communicate options, trade-offs, dependencies, cost implications, and recommendations.

Required Experience

- 10-15 years in enterprise, solution, cloud, data, or AI architecture, with leadership of complex transformation programs.

- Deep architecture experience in GenAI, LLMs, prompt engineering, RAG, AI agents, multi-agent systems, MCP, tool calling, and function calling.

- Expertise across Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.

- Solid track record in enterprise integration, API architecture, cloud-native patterns, MLOps, observability, security, resilience, and architecture governance.

- Banking or financial-services architecture experience strongly preferred across retail, corporate, trade finance, digital banking, risk, and compliance.

Required Skills

Skill Group

Required Skills

Technical Skills





Enterprise AI architecture; GenAI and LLM architecture; Prompt and RAG patterns; Agentic and multi-agent architecture; MCP; Tool calling; Function calling; Evaluation architecture

Platform Skills

Azure OpenAI; Azure AI Foundry; Azure AI Search; Azure Functions; AKS; Azure API Management; Microsoft Fabric; Cloud-native architecture

Integration Skills

API and microservices architecture; Event-driven architecture; Identity architecture; Data integration; Legacy and SaaS integration

Governance Security Skills

Responsible AI; AI governance; Security and compliance architecture; Model risk controls; MLOps; Observability; Enterprise architecture standards

Leadership / Business Skills

Technology strategy; Architecture governance; Executive advisory; Commercial assessment; Vendor management; Roadmapping; Influencing across functions

Preferred Tools and Certifications

Certification

Relevance

Requirement

Microsoft Certified: Azure Solutions Architect Expert

Design secure, resilient, and scalable Azure solutions.

Strongly Preferred

Microsoft Certified: Azure AI Engineer Associate

Design and implement Azure AI capabilities.

Preferred

TOGAF Certification

Apply enterprise architecture methods and governance.

Preferred

Kubernetes Certification

Architect and govern containerized workloads on AKS.

Preferred

Generative AI Architect Certification

Design enterprise GenAI, RAG, and agentic solutions.

Preferred

Education

Bachelor s degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related discipline is mandatory. A Master s degree in a relevant technical or business field is preferred.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Architect (Mumbai)
🏢 Crisil
📍 Mumbai