Deployment Engineer

Leidos•Columbus, OH

About The Position

Kudu Dynamics, a Leidos-owned company, is seeking a hands-on Deployment Engineer to install, configure, validate, and support its AI-powered autonomous vulnerability operations platform across customer on-premises, air-gapped and classified networks, hosted SaaS, and Leidos cloud-hosted infrastructure. The role focuses on standing up systems in varied environments, ensuring they run reliably, and documenting their operation so customer and internal teams can support them. The engineer will work across Kubernetes, LLM endpoints, and Linux systems, including workloads that run for extended periods, retry, and may produce non-deterministic results. This role partners with platform engineering and Cyber Agent development teams, supports customers in reaching a healthy operating state, and feeds lessons from deployments back into the product. It is an individual-contributor role, not a supervisory position. The engineer will design and maintain Linux and Kubernetes infrastructure, build repeatable deployment workflows using infrastructure-as-code, improve monitoring and operational resilience, automate routine tasks, diagnose issues across infrastructure and distributed systems, and support operational standards, upgrades, recovery, and capacity planning. The position also involves documenting deployments and training customer and internal teams. During the first 90 days, the engineer is expected to learn the platform's scan lifecycle, work with the Temporal and Kubernetes execution plane, complete an end-to-end deployment, improve observability, document a repeatable deployment runbook, contribute to a failure taxonomy, and validate backup and restore in a representative environment. The role requires at least three years of relevant deployment, systems/platform, DevOps, or production infrastructure experience; hands-on Kubernetes and Docker operation; Linux administration; experience supporting workloads that call LLM endpoints; backup and recovery, monitoring, automation, and documentation skills; scripting ability; eligibility to obtain and maintain a U.S. government security clearance; and U.S. citizenship. Preferred qualifications include virtualization and cluster experience, workflow orchestration, database operations, NixOS, service-level objectives, CPU/GPU scheduling, workload isolation, classified-environment delivery, NIST RMF, DevSecOps/security tooling, an active clearance, and relevant certifications.

Requirements

At least 3 years of experience 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, including multi-node clusters; examples include MicroK8s and K3s.
Proficiency administering Linux systems and troubleshooting networking, storage, and containers.
Experience deploying or supporting workloads that call internal or external LLM endpoints, including reasoning about rate limits, provider failures, and model serving.
Experience building and testing backup and recovery processes so deployed systems can be reliably restored.
Experience building monitoring, logging, and alerting to detect problems 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 skills, including capturing system architecture and training others to operate and troubleshoot deployments.
Scripting or programming ability, such as Python, sufficient to automate deployment and connect systems.
Ability to obtain and maintain a U.S. government security clearance.
U.S. citizenship required.

Nice To Haves

Experience with Proxmox or other virtualization and self-hosted compute clusters.
Familiarity with durable workflow orchestration systems 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.
Experience defining Service Level Indicators/Objectives and error budgets.
Experience with CPU/GPU scheduling for compute-intensive workloads, including capacity and utilization telemetry.
Experience with 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, including ATO or 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+.

Responsibilities

Install, configure, and validate the platform in customer on-premises, air-gapped/classified, SaaS, and cloud environments.
Design, deploy, and maintain the Linux and Kubernetes infrastructure used by the platform.
Build reproducible configurations and deployment workflows using infrastructure-as-code.
Establish 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 analyzed software.
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 deployments and train customer and internal teams to operate them.
Learn the scan lifecycle and how units of work move through the platform.
Gain hands-on experience with the Temporal and Kubernetes execution plane and complete an end-to-end deployment.
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.
Share knowledge and teach other team members.