Chief AI & DevOps Architect

Job Description

Role Overview

We are seeking an experienced Chief AI & DevOps Architect to define, govern, and lead the enterprise‑wide AI architecture, AI‑driven development practices, and secure AI platform foundation. This role carries end‑to‑end accountability for ensuring that artificial intelligence is designed, built, and operated in a Safe AI‑by‑default manner, aligned with regulatory, security, and economic constraints of a large enterprise.

The Chief AI & DevOps Architect is the highest technical authority for AI architecture and AI‑driven software delivery, with deep expertise in Microsoft Azure and the Microsoft security stack. The role is pivotal in building enterprise capability, leading transformation, and embedding security and compliance into every layer of AI‑enabled development.

This role requires strong hands‑on expertise and the ability to operate at both strategic and implementation levels.

Key Responsibilities

Enterprise AI Architecture & Strategy

• Define and own the enterprise AI architecture, including reference architectures, architectural guardrails, and design principles.
• Design and evolve Azure‑based AI platform architectures that support model development, deployment, inference, monitoring, and lifecycle governance at enterprise scale.
• Ensure AI solutions are secure, resilient, scalable, auditable, and cost‑efficient, suitable for mission‑critical and regulated workloads.
• Act as the ultimate architectural escalation point for AI, DevOps, and security‑related design decisions.

Safe AI Development Environment

• Leading the transition to AI‑driven software development practices.
• Design and establish a Safe AI development environment for the enterprise, covering:

• Secure development workspaces
• Controlled data access and isolation
• Model usage policies and architectural guardrails
• Traceability, auditability and accountability
• Ensure Safe AI practices are embedded across the full development lifecycle and aligned with internal risk management, legal, and compliance expectations.
• Understand and actively manage the financials and economics of AI platforms together with AI solution Engineer who owns AI platforms, including:
• Cloud consumption and cost drivers
• AI service and model usage economics
• Scalability, efficiency, and cost‑control mechanisms
• Provide guidance to leadership on AI related investments, cost transparency, and sustainable AI and DevOps operating models.

AI‑Driven Software Development Lifecycle & Transformation Leadership

• Leading enterprise‑wide expertise on AI‑enabled software development lifecycle and DevOps practices, guiding the secure and responsible integration of AI into modern software engineering.
• Lead the transformation required to embed AI into development practices, pipelines, tooling, and operating models—with security engineered in from the start.
• Define standards and practice for:
• AI‑assisted development
• Secure CI/CD pipelines
• Release governance and quality controls for AI‑enabled software
• Define standards and practices for:

• AI‑assisted development
• Secure CI/CD pipelines
• Release governance and quality controls for AI‑enabled software

• Build enterprise‑wide capability by mentoring other architects, engineers (both internal and external), and platform teams, and by driving consistent ways of working. Work closely with Data & AI team to who owns the business AI development pipeline and AI governance.

Cloud, DevOps & Infrastructure Architecture

• Design and govern Microsoft Azure‑centric AI, DevOps, and cloud architectures, leveraging Azure AI services, Azure Machine Learning, Azure OpenAI, and supporting data platforms.
• Lead platform, environment, and pipeline provisioning using Infrastructure‑as‑Code (IaC), ensuring consistency, repeatability, security, and audit readiness.
• Partner with platform, cloud and infrastructure teams to ensure AI and DevOps architectures align with enterprise cloud strategy and operating models.

Security, Risk & Compliance

• Embed security expertise directly into AI and DevOps architecture and software development lifecycle design, rather than treating it as a separate control layer.
• Apply deep knowledge of the Microsoft security stack, including:

• Entra ID
• Microsoft Defender and other security services
• Identity and access management, privileged access, conditional access
• Data protection, key management, and secrets handling
• Purview
• Ensure AI‑enabled software meets regulatory, privacy, and security requirements, including data sovereignty, access control, logging, and auditability.
• Work closely with CISO team to ensure AI and DevOps adoption is secure, governed, and regulator‑ready.

Leadership & Stakeholder Engagement

• Lead the adoption of AI‑enabled software development across Aktia and its vendor ecosystem.
• Serve as a trusted advisor to executive leadership on AI, DevOps, security, and platform strategy.
• Translate complex architecture and security topics into actionable decisions for senior stakeholders.
• Contribute to technology roadmaps, sourcing strategies, and long‑term AI and engineering capability planning.

Required Qualifications

Experience & Background

• Several years of proven success in architecture roles, responsible for enterprise‑scale platforms and complex systems.
• Demonstrated experience designing and operating AI platforms and DevOps capabilities in production.
• Experience in financial services or other highly regulated environments is highly valued.

Technical Expertise

• The role requires hands‑on experience with AI‑assisted development tools such as GitHub Copilot and Claude Code, and the ability to apply them effectively within enterprise software development practices.
• The role requires proven experience in designing and implementing agentic AI teams and swarms to support AI‑enabled software development at enterprise scale.
• Expert‑level Microsoft Azure skills, particularly across AI, cloud platforms, identity, and security services.
• Strong hands‑on experience with Infrastructure‑as‑Code (IaC) in enterprise environments.
• Deep understanding of AI‑driven software development lifecycle, DevOps practices, and secure software engineering.
• Solid understanding of AI and platform economics, cloud cost structures, and scalability trade‑offs.

Certifications (Strong Plus)

• Microsoft Azure certifications (e.g. Azure Solutions Architect Expert, Azure AI Engineer, Azure DevOps Engineer Expert, Azure Security Technologies).

Interested?

If you're excited about this role, please submit your CV.
Please be aware that background checks (such as security clearance, credit check and drug test) are part of our recruitment process for the person to be recruited due to regulatory requirements.