Platform Engineer

Job summary

Build and operate a production, multi-tenant Kubernetes platform spanning cloud infrastructure, cluster operations, service mesh, GitOps delivery, and tenant-facing applications. Own initiatives from design through production, including infrastructure automation, progressive delivery, zero-trust security, and observability. Develop AI-driven workflows and agents to automate platform operations and improve engineering processes.

Qualifications

• At least 3 years of platform, infrastructure, DevOps, or SRE experience.
• Infrastructure-as-code experience with tools such as Terraform, Pulumi, Crossplane, or CloudFormation.
• Production experience deploying, operating, and debugging containers and Kubernetes workloads.
• Experience with at least one major cloud provider: AWS, Azure, or GCP.
• Experience with CI/CD and GitOps or other declarative delivery models.
• Networking fundamentals, including DNS, TLS, load balancing, and service traffic flows.
• Working knowledge of OIDC, OAuth 2.0, and JWTs.
• Programming experience in at least one modern language, with willingness to work in Go, Python, and TypeScript.
• Enthusiasm for AI-assisted development and trying new tools.
• Strong initiative, follow-through, and written communication skills.
• U.S. citizenship required.
• Ability to obtain a Secret clearance may be required.

Responsibilities

• Design, build, and operate cloud infrastructure as code across multiple accounts and environments.
• Operate production multi-cluster Kubernetes, including cluster lifecycle, upgrades, access control, admission policies, and custom resources.
• Automate customer environment creation end to end.
• Own delivery from commit to production, including CI pipelines, image builds, rendered configuration, and GitOps synchronization.
• Build safe environment promotion and progressive delivery with metrics-driven automated rollback.
• Operate the service mesh, including cross-cluster routing, mutual TLS, and tenant traffic isolation.
• Implement zero-trust controls, including policy enforcement, certificate management, workload identity, secrets management, and runtime threat detection.
• Maintain metrics, logs, and alerting across clusters.
• Build agents that analyze operational signals, triage problems, and propose fixes.
• Design and roll out AI agents, skills, and workflows for the engineering team.
• Build AI product features and internal tools.
• Lead platform initiatives from design through delivery and coordinate with product, application, and test engineers.

Skills

Certifications

Degrees

Languages

Industry

Security clearance

Relocation