Staff Engineer

Role overview

Help deploy and operate data, AI, and software platforms across cloud, on-premises, disconnected, and tactical environments. The work spans Kubernetes infrastructure, delivery automation, security practices, observability, and operational support for data and machine-learning services. It is suited to an engineer who can take ownership of clearly scoped platform tasks while expanding toward broader operational responsibility.

Responsibilities - Maintain and troubleshoot Kubernetes infrastructure, workloads, networking, storage, and service configuration. - Build and support CI/CD and GitOps workflows, managing deployment configuration with tools such as Helm and related systems. - Apply secure delivery controls, including container hardening, vulnerability scanning, image checks, secrets handling, and policy gates. - Support deployments across public cloud, data centers, and disconnected or edge settings; investigate service and runtime issues. - Improve monitoring and logging, and coordinate with software and data engineers to understand dependencies and failure modes. - Create small automation tools, document operational procedures, and contribute to compliance-focused delivery practices.

Requirements - Around five years of relevant experience in DevOps, DevSecOps, platform engineering, infrastructure, systems administration, or security engineering. - Working knowledge of Linux, containers, Docker, Kubernetes, and common workload concepts such as pods, services, deployments, and ingress. - Experience supporting CI/CD pipelines and exposure to infrastructure-as-code or configuration tools. - Understanding of core security practices, including least privilege, vulnerability management, secure configuration, secrets handling, and auditability. - Ability to investigate logs and runtime behavior, use command-line tools, script in a common language, and document findings clearly. - Active Secret clearance and eligibility for TS/SCI are required. U.S. citizenship is required for the supported programs, and work must be performed within the continental United States.

Nice to have

Exposure to streaming data, MLOps, or AI/ML workloads is useful; examples in the listing include Kafka, Flink, KServe, Kubeflow, and Ray. Familiarity with observability tooling and compliance frameworks such as RMF, STIGs, or NIST 800-53 may also help.

Benefits and work setup

The listing gives a salary range of $120,000–$160,000 and describes a hybrid role in Hawaii with up to 30% travel. Benefits include health, dental, and vision coverage, a 401(k) with company match, paid holidays, flexible paid time off, education and training support, and referral bonuses.