Enterprise Architect – AI Architect

Overview

The Role Is Responsible For

• Defining and evolving architecture mechanisms, standards, patterns, and reference architectures
• Owning the software and technology catalog for the domain, including Invest / Hold / Disinvest lifecycle positioning
• Driving adoption and consistent application of EA standards and practices in close collaboration with Technology Owners and Application Teams
• Providing thought leadership and clear long‑term architectural direction for the domain
• Defining and maintaining multi‑year architecture and technology roadmaps, aligned with business strategy and regulatory priorities
• Leveraging automation and AI‑enabled approaches to simplify, modernise, and scale EA governance, standards management, and overall EA capabilities
• The role works closely with business stakeholders, Technology Owners, application and delivery teams, and governance bodies to ensure that enterprise and domain‑level architectures are robust, scalable, secure, compliant, and future‑ready.

Future‑State Architecture & Platform Strategy

• Define and evolve the future‑state architecture for the assigned domain, including architecture principles, standards, patterns, and reference architectures.
• Establish clear architectural mechanisms and positions that guide how technologies are selected, used, and evolved within the domain.
• Define strategic technology and platform direction, including modernization, consolidation, and managed exit of legacy technologies.
• Develop architecture position papers, option analyses, and target‑state roadmaps to support executive and governance decision‑making.
• Ensure architectural direction consistently addresses scalability, resilience, security, data protection, regulatory compliance, and operational sustainability.
• Contribute to enterprise‑level architecture initiatives and overall EA practice maturity uplift.

AI Domain Architecture

• Define and evolve the enterprise AI architecture foundations, including platforms, and reference architectures
• Own standards and patterns for AI/ML, GenAI, MLOps, LLMOps, Agentic …
• Maintain the AI technology catalog, including lifecycle positioning of AI capabilities
• Define long‑term AI evolution roadmaps, balancing innovation with governance, trust, and operational sustainability
• Drive adoption of approved AI architectures across application and platform teams

Software/Technology Catalog & Lifecycle Management

• Own the domain software and technology catalog, in collaboration with Technology Owners.
• Define Invest / Hold / Disinvest lifecycle positioning with clear architectural rationale.
• Ensure lifecycle intent is reflected in:
• Architecture standards and patterns
• Architecture governance decisions
• Long‑term modernization and rationalisation roadmaps
• Prevent uncontrolled technology sprawl and duplication.

Architecture Strategy, Adoption & Governance

• Define and enforce architecture guardrails to drive standardisation, reuse, resilience, and security‑by‑design.
• Govern solution and platform designs through EA governance forums (e.g. EADA), focusing on alignment to standards, patterns, and approved catalog technologies.
• Drive early and consistent adoption of architecture guidance across Technology Owners and Application Teams.
• Manage non‑standard designs through alignment or formally governed exceptions.
• Continuously improve architecture standards and governance mechanisms based on business evolution, delivery feedback, and operational insights.

EA Capability Modernisation & Thought Leadership

• Act as a trusted domain authority and source of architectural thought leadership.
• Monitor industry trends and emerging technologies to inform pragmatic architectural evolution.
• Guide appropriate architectural style shifts while balancing innovation with regulatory and operational readiness.
• Identify and promote the use of automation and AI‑enabled approaches to simplify, scale, and industrialise EA mechanisms (standards management, governance, reviews, insights).

Collaboration & Stakeholder Engagement

• Work closely with Technology owners to align architecture direction, lifecycle intent and platform roadmaps.
• Engage with Application Team and Solution Architects to provide early guidance
• Collaborate with internal governance bodies (e.g., Cloud, Data, Security) to ensure coherence across domains.
• Engage with vendors and strategic partners to assess solutions and ensure alignment with enterprise and domain architecture direction

Required Qualifications And Skills

• Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience).
• 15+ years of experience in Enterprise Architecture, Domain Architecture, or Solution Architecture roles within complex, large‑scale environments.
• Strong and proven technical foundation built through hands‑on engineering experience, typically progressing from roles such as system administration, software engineering, platform engineering, or DevOps into architecture roles.
• Proven experience defining future‑state architectures and driving strategic platform decisions, including technology evaluation and target‑state
• Proven hands-on expertise in AI/ML engineering and GenAI, MLOps, AIOps, AI Model life cycle management, Agentic System Design
• Proven experience in Data architecture,
• Proven experience in Public Cloud platform with Hybrid integration (AWS, Azure), across the AI, GenAI services
• Familiarity with security protocols and data protection standards in banking environments (e.g., OAuth2, TLS, PKI, DLP).
• Demonstrated ability to design architectures grounded in real‑world delivery, operational, and production experience — not purely theoretical models.
• Demonstrated experience operating within regulated, banking‑grade environments.
• Proven ability to influence architectural outcomes across multiple delivery teams without direct delivery ownership.
• Strong working knowledge of relevant domain platforms and technologies (e.g., cloud platforms, containers, databases, middleware, security tooling, platform services).
• Solid understanding of security‑by‑design, regulatory compliance, and risk considerations.
• Certification from Cloud provider is a plus (AWS, Azure)
• Familiarity with Enterprise Architecture frameworks (e.g., TOGAF) is a plus.
• Experience working within Agile / DevOps delivery models.
• Excellent analytical, communication, and stakeholder‑management skills.
• Ability to operate effectively in complex, fast‑paced, cross‑functional environments.
• Relevant architecture or domain certifications are an advantage.