Secure Traces
Website:
securetraces.com
Job details:
We are scaling our proprietary AI governance framework into a hardened, enterprise-ready cloud platform. This role is not about maintaining a legacy system; it’s about architecting the next-generation infrastructure, security protocols, and high-velocity deployment pipelines required to solve one of the most critical risks in modern technology.
As our Lead DevSecOps Engineer, you will own the production architecture, establishing a secure-by-default environment capable of running high-performance AI governance workloads for enterprise clients.
What You’ll Do
- Architect Enterprise Infrastructure: Design and implement the scalable cloud infrastructure and zero-trust security framework capable of hosting our core AI governance systems.
- Build Hardened Pipelines: Establish highly secure, automated Kubernetes environments and CI/CD pipelines where security controls (SAST, DAST, and container scanning) are natively integrated.
- Own the Infrastructure as Code (IaC): Standardize deployment environments using Terraform or Pulumi to ensure total repeatability, modularity, and environment isolation.
- Optimize Cloud Economics: Drive efficiency by tracking cloud spend, architecting resource-optimized clusters, and aligning infrastructure overhead directly with our product pricing models.
- Automate Security Guardrails: Implement automated vulnerability management and continuous compliance monitoring for both application code and the underlying AI models.
What You Need to Bring
- Production-Grade Builder Mentality: Proven experience taking complex software systems and scaling them into production-ready, enterprise-grade cloud environments.
- Deep Cloud & Kubernetes Orchestration: Expert-level mastery of major cloud ecosystems (AWS, GCP, or Azure) and hands-on capability in managing, scaling, and troubleshooting production Kubernetes clusters.
- Security & Compliance Obsession: Strong background in threat modeling, IAM policy design, data encryption (at rest and in transit), and alignment with compliance frameworks (SOC2, ISO 27001, etc.).
- Financial and Operational Logic: A sharp eye for cloud economics. You can analyze a bill, eliminate architectural waste, and provide engineering metrics to help optimize margins.
- Technical Autonomy: High-agency engineer who thrives with complete ownership, capable of driving architecture independently or leading a lean team as the platform expands.
Knowledge Expectation
- Cloud: Major Cloud Providers (AWS / GCP / Azure)
- Orchestration: Kubernetes / Docker / Container Security Tools
- Infrastructure: Terraform / Pulumi / Terragrunt
- Security: Secret Management (Vault), IAM, Automated Compliance & Vulnerability Scanners
Why Join Us Now?
While the industry is just beginning to define AI risk, we are deploying the infrastructure to manage it. You will step into a high-ownership position with a definitive seat at the table, directly shaping our technical choices, operational culture, and long-term architecture.
If you are ready to build the security engine for safe enterprise AI, let's chat.
Click on Apply to know more.