Senior Staff Security Engineer

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.

About the Role

We're looking for a Senior Staff Platform Security Engineer to set and deliver the technical direction for platform and AI security at VDC . Veeam VDC Security Engineering builds and operates the security platform for a multi-cloud (Azure and AWS) SaaS serving regulated industries. This role sits in Platform and AI and partners with the other technical leads on the team across three areas that decide how much risk ships with every release: software supply chain, secure AI sandboxes, and vulnerability management. You'll partner with Product Engineering, SRE, Corporate Technology and Compliance, and you'll be measured on mechanisms delivered rather than advice given.

What You’ll Do

Partner with the other technical leads on the team to drive software supply chain security across Veeam SaaS platforms

Engineer secure AI practices and patterns for Veeam SaaS platforms

Partner with the other technical leads on the team to run vulnerability management as an engineering system

Deliver security controls as Terraform

Build the automation that reduces operational toil

Raise the engineering bar across the team

Participate in an on-call rotation

Technologies You’ll Work With

Terraform as the primary control plane for security infrastructure

Azure: Entra ID and RBAC , Key Vault, Azure Policy, Defender for Cloud, Container Instances, AKS , Container Registry, managed identity and workload identity federation AND AWS equivalents

CSPM for cloud and workload posture, attack paths and container findings

ASPM for SAST , SCA , secrets and IaC scanning in the pipeline

GitHub Actions, GitHub Apps and Azure DevOps for CI/CD

Supply chain provenance tooling: SBOM (CycloneDX or SPDX ), artifact signing and attestation (Sigstore / cosign), SLSA -aligned build integrity

Anthropic Claude and Azure OpenAI

Python and Go for the tooling stack, with comfort reading PowerShell and TypeScript

Microsoft Sentinel and Log Analytics for the audit trail

What You’ll Bring

8+ years across security and engineering, with recent depth in cloud platform security and hands-on delivery

Production Terraform at scale. Modules other teams consume, not one-off stacks, and the judgment to know when a control belongs in code rather than a runbook

AI and LLM security specifically: prompt injection, indirect prompt attack surfaces, agent tool-boundary abuse, model exfiltration

Deep Azure: Entra ID and RBAC , Key Vault and key handling, network egress, workload and managed identity, policy enforcement, and a clear view of where the platform defaults leave you exposed

Software supply chain security in practice: dependency risk, build pipeline integrity, provenance and signing, and the judgment to know which controls are worth the developer friction they cost

Owned vulnerability management as an engineer, not a coordinator: ingestion, deduplication, routing, SLA design, and measurable reduction rather than a dashboard

Designed isolation boundaries for untrusted code execution, covering network, identity and data, with a threat model you can defend

Tooling ability in Python or Go sufficient to build and maintain systems rather than only configure vendor products

A track record of setting technical direction others followed, and of shipping production code you can point to. Thi