DevSecOps

Build and secure the cloud platforms that AI-powered enterprise applications run on, from CI/CD pipelines to LLM deployment infrastructure.

You'll design and own secure cloud infrastructure for AI workloads at enterprise scale. That means building CI/CD pipelines with security baked in from the start, writing Terraform to provision and govern cloud environments, and making sure LLM applications and ML pipelines are properly secured before they go anywhere near production. You're the person who makes it possible for development teams to ship fast without cutting corners on security.

The work sits across AWS, Azure or GCP, so you'll get exposure to real multi-cloud complexity rather than a single-vendor setup. The team includes platform engineers, AI engineers, security architects and software developers, so there's genuine depth around you. You'll be writing Python, Bash or Go to automate security controls and build guardrails into infrastructure, using tooling like GitHub Actions or Azure DevOps for CI/CD and CSPM or CNAPP platforms to keep cloud posture in check.

This is a senior role with real scope. You'll shape how DevSecOps practices get embedded across the engineering org, mentor other engineers, and have meaningful input into AI governance frameworks covering model security, prompt protection and data privacy. The work is genuinely varied, and the AI infrastructure side of it is still being built out, so there's room to define how things are done rather than inheriting someone else's decisions.

What You'll Do

• Design and build secure CI/CD pipelines for cloud-native and AI workloads using GitHub Actions, GitLab CI or Azure DevOps.
• Write Terraform to build and govern cloud infrastructure, including policy-as-code, automated remediation and security guardrails.
• Secure AI platforms and ML deployment pipelines, including LLM applications, prompt protection and model security controls.
• Integrate automated security testing across the SDLC, covering SAST, DAST, SCA, container scanning and IaC scanning.

What You'll Need

• Solid background in DevSecOps, Platform Engineering or Cloud Engineering, with hands-on AWS, Azure or GCP experience.
• Strong Terraform skills and experience building enterprise CI/CD pipelines with security tooling integrated throughout.
• Docker and Kubernetes experience, including container and Kubernetes security, plus working knowledge of IAM, RBAC, Secrets Management and PKI.
• Scripting ability in Python, Bash or Go, and familiarity with monitoring and observability platforms.

About the Company

They're building cloud platforms that support enterprise-scale AI application development and deployment. The engineering team spans platform, cloud, security and AI disciplines, and they're at a stage where the infrastructure is actively being built out rather than just maintained.

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