Lead DevSecOps Engineer

Overview

In this AI Engineering role, you guide DevSecOps for multi-cloud platforms, shaping secure, reliable pipelines and scalable infrastructure. You’ll collaborate with platform, product, and AI/ML teams to accelerate delivery while embedding security and governance by design. Your work enables faster, safer deployment of AI-powered infrastructure solutions that reduce waste and boost sustainability. This is a hands-on, high-impact role within a lean, technically driven team backed by a global engineering firm.

Pay / Benefits

• comprehensive benefits package
• potential for flexible work options
• retirement savings plan
• employee stock purchase plan
• voluntary benefits
• well-being resources

Responsibilities

• Lead DevSecOps capabilities across CI/CD, IaC, observability, and cloud governance for Azure and GCP
• Evolve CI/CD pipelines and reusable workflows with automated quality and security controls
• Build observability and incident readiness to improve production reliability and performance
• Define and track service reliability objectives and conduct post-incident reviews
• Embed security into engineering workflows, including threat modelling, secrets management, and vulnerability remediation
• Monitor cloud security posture and prioritize remediation across Azure and GCP
• Manage vendor relationships with Microsoft, Google Cloud, and other key providers for reviews, escalations, and roadmap discussions
• Collaborate with platform, product, and AI/ML engineers on architecture decisions and mentor peers

Key requirements

• Hands-on experience in DevOps, SRE, platform engineering, or DevSecOps
• Experience building and maintaining CI/CD pipelines (GitHub Actions or similar)
• Proficiency with Infrastructure as Code and Terraform
• Proven ownership of production reliability, observability, and incident management
• Security reviews and controls across identity, secrets management, software supply chains, and vulnerability management
• Experience with cloud providers (Microsoft, Google Cloud) including service reviews and escalations
• Experience optimizing cloud expenditure in large Azure or GCP environments

• Mentoring and leadership
• Cross-functional collaboration
• Problem-solving orientation
• GitHub Actions
• Terraform
• Infrastructure as Code

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