Who We Are:

Kudu Dynamics is a Leidos owned company, forged out of a decade of experience in computer network operations and staffed with talent who have built, overseen, and enhanced capabilities throughout the entire USG arsenal. Our team of hackers, engineers, makers, and shakers have expe­rience spanning centuries of research, development, and oper­ations missions - across desktop, mobile, IoT, and embedded platforms. Kudu Dynamics is uniquely qualified to anticipate tomorrow’s threats and build the next of capabilities.

Summary:

We’re an innovative, forward-looking team seeking a Deployment Engineer to install, configure, and support our AI-powered, autonomous vulnerability operations platform across the environments our customers run in — including customer on-premises installations, air-gapped and classified networks, a hosted software-as-a-service offering, and Leidos cloud-hosted infrastructure.

This role is for a hands-on engineer who enjoys standing systems up, making them run reliably in someone else’s environment, and leaving behind clear documentation so others can operate what you deploy. You are comfortable working across Kubernetes, LLM endpoints, and Linux systems, and you are at ease with workloads that run for hours, retry, and return non-deterministic results. You’ll partner closely with platform engineering and the Cyber Agent development teams, help customers get to a healthy running state, and feed what you learn in the field back into the product. We’re a collaborative team working at the leading edge, and we’re looking for someone who wants to both learn and lead. This is not a supervisory role.

Required Experience:

• 3+ years in deployment engineering, systems/platform engineering, DevOps, or production infrastructure, including hands-on responsibility for standing up and supporting running systems.
• Hands-on experience deploying and operating containerized workloads with Kubernetes and Docker (e.g., MicroK8s, K3s, or equivalent), including multi-node clusters.
• Proficiency administering Linux systems, with practical troubleshooting across networking, storage, and containers.
• Experience deploying or supporting workloads that call internal or external LLM endpoints, and comfort reasoning about rate limits, provider failures, and model serving.
• Experience building and testing backup and recovery so deployed systems can be restored reliably.
• Experience building monitoring, logging, and alerting so problems are caught before customers notice them.
• Experience automating repetitive setup and configuration tasks and reducing configuration drift.
• Comfort operating long-running, highly parallel, retried, and non-deterministic jobs, including partially completed work and checkpointing.
• Strong documentation habits — able to capture system architecture and train others to operate and troubleshoot what you deploy.
• Scripting/programming ability (e.g., Python) sufficient to automate deployment and glue systems together.
• Ability to obtain and maintain a U.S. government security clearance. U.S. citizenship required.

What You’ll Do:

• Install, configure, and validate the platform across customer on-premises, air-gapped/classified, SaaS, and cloud environments.
• Design, deploy, and maintain the Linux and Kubernetes infrastructure the platform runs on.
• Build reproducible configurations and deployment workflows using infrastructure-as-code.
• Stand up monitoring, logging, and alerting, and improve resilience, recoverability, and maintainability.
• Diagnose failures across Linux, networking, storage, containers, and distributed systems — and help distinguish platform failures from issues in the software being analyzed.
• Automate operational tasks, eliminate configuration drift, and harden deployed systems.
• Contribute to operational standards, deployment practices, upgrade strategies, and backup/disaster-recovery procedures.
• Perform capacity planning and identify performance bottlenecks across compute, storage, and networking.
• Document everything you deploy and train customer and internal teams to operate it.
• Learn new skills and teach the rest of us what you know.

Your First Ninety Days:

• Learn the scan lifecycle and how a unit of work moves through the platform.
• Get hands-on with the Temporal and Kubernetes execution plane and a full deployment end to end.
• Stand up (or improve) monitoring and the observability model for a deployed environment.
• Document a repeatable deployment runbook and contribute to the failure taxonomy.
• Validate backup and restore in a representative environment.

Preferred Qualifications:

• Experience with Proxmox or other virtualization, and self-hosted compute clusters.
• Familiarity with a durable workflow orchestration system such as Temporal, including diagnosing stuck, retried, and non-retryable executions.
• Experience operating Postgres, ClickHouse, or Redis.
• Familiarity with NixOS, Nix flakes, and reproducible system configuration.
• Exposure to defining Service Level Indicators/Objectives and error budgets.
• CPU/GPU scheduling for compute-intensive workloads, with capacity and utilization telemetry.
• Workload isolation and ephemeral execution environments for untrusted or potentially hostile software.
• Prior experience delivering software into classified, air-gapped, or disconnected government environments.
• Familiarity with NIST RMF accreditation activities (ATO / continuous ATO).
• Familiarity with DevSecOps pipelines and security tooling (SAST, DAST, SCA), or vulnerability-management workflows.
• Active U.S. government security clearance.
• Certifications such as Certified Kubernetes Administrator, a cloud architect/engineer credential, or Security+.

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo — because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 — and moving faster than anyone else dares.

Original Posting:

Pay Range:

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.