Lead Engineer (Cloud & DevOps)

Job summary

The Lead Engineer provides technical leadership for Azure Cloud and DevOps Managed Services and coordinates improvements across related service lines. The role turns a strategic transformation agenda into engineering roadmaps, standards, quality gates, and measurable improvements in automation, reliability, and operational efficiency, using Azure, Terraform, Bicep, CI/CD, observability, SRE, and DORA-aligned practices. It also guides the responsible introduction of AI-assisted workflows and agents, with appropriate testing, governance, and human oversight.

Benefits

Qualifications

• Demonstrated technical leadership in Azure Cloud and DevOps environments.
• Hands-on knowledge of Azure architecture, governance, identity, networking, security, Terraform, Bicep, CI/CD, observability, and operational support.
• Experience leading technical change across multiple teams without relying solely on direct line-management authority.
• Ability to turn strategic transformation goals into practical engineering priorities, standards, and measurable deliverables.
• Understanding of deterministic automation, AI-assisted workflows, and responsible use of AI agents.
• Experience with DevOps, SRE, DORA metrics, production readiness, service reliability, and continual improvement.
• Ability to identify and quantify operational toil, prioritise automation, and measure resulting improvements.
• Strong stakeholder and consulting skills across technical, commercial, service, and client teams.
• Commercial awareness and ability to balance technical quality, operational risk, delivery capacity, and client outcomes.
• Strong documentation skills and ability to establish reusable standards, patterns, runbooks, and technical controls.
• Experience with Modern Workplace and enterprise networking is desirable.

Responsibilities

• Lead technical delivery across Azure Cloud and DevOps Managed Services, coordinating with Modern Workplace and Networking.
• Translate strategic goals into a prioritised roadmap for automation, AI agents, service modernisation, observability, reliability, and operational efficiency.
• Identify repetitive operational work and prioritise automation, AI-assisted operations, self-service, and agentic workflows.
• Establish reusable engineering standards, reference architectures, patterns, guardrails, and technical controls.
• Coordinate the technical improvement backlog, balancing client commitments, operational risk, service improvements, and transformation priorities.
• Guide engineers across service lines and partner with people leaders to address capability gaps.
• Embed DevOps, infrastructure as code, SRE, and DORA-aligned practices into service delivery and continuous improvement.
• Define technical quality gates for onboarding, production readiness, security, supportability, documentation, and service transition.
• Measure and communicate improvements in automation, reliability, deployment performance, operational toil, service quality, and client outcomes.
• Provide senior technical input on complex incidents, problem management, architecture decisions, and service risks.
• Maintain testing, auditability, governance, and human oversight for AI agents and automated production workflows.
• Support client-facing technical engagements, service reviews, solution development, and growth opportunities.

Skills

Certifications

Relocation