We're expanding our DevSecOps team. You'll build secure delivery pipelines, run infrastructure as code on AWS, keep our Kubernetes workloads reliable — and help bring every team along to the same standard.

What will you do

• Build and maintain CI/CD pipelines (GitHub Actions) with a shift-left approach — security and quality scanning (SAST, dependency/SCA, secrets, container images) integrated from the developer's machine through every stage of the SDLC.
• Build, improve, and maintain infrastructure as code with Terraform/Terragrunt on AWS, following the Landing Zone Architecture.
• Bring the agentic AI age into every layer of our work — apply AI coding agents and automation across CI/CD, code, and cloud infrastructure so we build and maintain systems more effectively, and help define the guardrails to use them safely.
• Operate containerized workloads on Kubernetes (EKS) and keep them secure, cost-effective, and reliable.
• Automate repetitive operational work — if we do it by hand more than once, you design the solution to solve it.
• Triage findings from security scanners and monitoring alerts; work with dev teams to verify fixes.
• Shine a light on the blind spots — build and tune monitoring, alerting, and availability dashboards so we know about issues before our customers do.
• Support security incident response — help investigate, contain, and follow up on findings through to remediation.
• Support compliance work — collect evidence, implement controls, and keep security configurations documented.
• Help drive adoption of DevSecOps standards across teams — demonstrate practices with working examples, document them clearly, and patiently bring skeptical teams on board.
  

Who we are looking for

• Bachelor's degree in Computer Science, Information Security, or a related field
• Hands-on with AWS (GCP a plus) — able to build, deploy, and maintain a service end to end
• Hands-on Kubernetes experience (we run EKS) and solid container fundamentals
• Scripting in Python, NodeJS, or shell
• Linux and networking fundamentals (TCP/IP layers, DNS, routing, firewalls) for troubleshooting
• Git-based workflows and CI/CD experience
• Hands-on use of AI-assisted engineering tools (coding agents, LLM tooling) in daily work — with the judgment to verify what they produce
• Automation mindset, systematic problem-solving, and self-drive — with something concrete to show for it
• Clear communicator who inspires teams to adopt new practices — leading with evidence and working examples, not authority

What's great if you have:

• Terraform/Terragrunt, GitHub Actions
• GitOps with ArgoCD
• Cloud security and OWASP basics
• Datadog or similar observability platforms
• Experience building agentic workflows — MCP integrations, AI-driven pipeline automation, or custom agents/skills
• Home lab, consistent self-paced learning, or open-source contributions