Engineer

Description

The role is based in the U.S. Every program the team supports requires U.S. citizenship for eligibility, and all work must take place within the continental United States.

The company is a non-traditional defense technology firm headquartered in McLean, Virginia. It builds AI, machine learning, and data solutions for U.S. military and government agencies and is a leader in autonomous data fusion and agentic AI. Its focus areas are distributed data systems, large-scale platforms, and complex application development. Its clients are federal and public agencies that work with design thinking, a modern tech stack, and cloud-native ecosystems.

The team builds data, AI, and operational platforms that support time-sensitive decisions across several classification levels and deployment environments. Systems move from cloud development environments into classified, on-premises, and edge deployments, where reliability, security, and repeatability matter.

As a DevOps Engineer, you will help secure, deploy, and run the platforms behind the team's data and AI work and its MLOps workflows. The role covers more than infrastructure: you will learn how the software works, how data flows through the platform, how Kubernetes workloads behave in production, and how security controls fit into daily delivery.

You will see CI/CD, GitOps, Kubernetes, Helm, observability, secure configuration, data pipelines, ML serving, and customer deployments in one workstream. You will work with platform, software, data, and security engineers and take ownership of well-scoped tasks. The ideal person is curious, disciplined, persistent in troubleshooting, and ready to take on wider platform ownership over time.

Success means reliably completing assigned deployment, automation, observability, and security tasks with clear communication. You explain what changed, why it changed, how it was verified, and what risk remains. You move from following runbooks to improving them, then to owning small platform improvements end to end. Senior engineers trust you with well-defined operational work because you investigate carefully and raise the right issues early. Security and compliance show up in your pipelines, manifests, secrets, images, documentation, and handoffs.

Responsibilities

• Implement, maintain, and troubleshoot Kubernetes platform infrastructure with guidance from senior engineers.
• Build and keep up CI/CD and GitOps workflows using tools like GitLab CI, Argo CD, Flux, and Helm, plus deployment configuration stored in repositories.
• Help with secure delivery through container hardening, vulnerability scanning, image provenance checks, secrets hygiene, and policy-driven deployment gates.
• Help run deployments in cloud, on-premises, and disconnected settings across AWS, Azure, data centers, and tactical environments.
• Deploy and debug services, Helm charts, service mesh configuration, Kubernetes networking, storage, and runtime behavior.
• Support observability with Prometheus, Grafana, Fluent Bit, Loki, Kibana, OpenTelemetry, or similar tools so issues are found and fixed quickly.
• Work with software and data engineers to map service dependencies, data flows, and operational failure modes.
• Support data and MLOps workloads, which may include Kafka, Flink, Pinot, KServe, Kubeflow, Ray, GPU-enabled workloads, and model serving.
• Write maintainable automation and small tools in Go, Java, Python, Bash, or similar languages to cut manual work and improve repeatability.
• Help deliver work aligned with RMF, STIGs, NIST 800-53, IL4/IL5/IL6, and customer-specific security requirements.
• Write operational procedures, deployment notes, troubleshooting steps, and lessons learned that other engineers can reuse.

Requirements

• 5 years of hands-on experience in DevSecOps, DevOps, platform engineering, cloud infrastructure, systems administration, cybersecurity engineering, or a closely related role.
• Working familiarity with Linux, containers, Docker, and Kubernetes concepts, including pods, services, deployments, config maps, secrets, ingress, and basic troubleshooting.
• Experience building, running, or supporting CI/CD pipelines, with exposure to GitLab CI, GitHub Actions, Jenkins, Argo CD, Flux, or similar tools.
• Exposure to Infrastructure as Code or configuration management using Terraform, Ansible, Helm, Kustomize, or similar tools.
• Understanding of core security practices: least privilege, vulnerability management, container image scanning, secrets handling, secure configuration, and auditability.
• Ability to read application logs, check runtime configuration, use command-line tools, and trace evidence to root cause.
• Basic scripting or programming in Go, Java, Python, Bash, or a comparable language.
• Strong written communication and willingness to document work clearly for teammates, customers, and future operators.
• Active Secret clearance required, and you must be eligible for and willing to obtain a Top Secret/SCI clearance.
• Ability to obtain Security+ certification within 90 days of starting.
• Ability to travel up to 30%.
• Highly preferred: hands-on experience deploying applications with Helm or Kustomize in a Kubernetes environment.
• Highly preferred: exposure to GitOps workflows and continuous delivery across multiple environments.
• Highly preferred: familiarity with AWS or Azure basics, including IAM, networking, storage, compute, and managed Kubernetes services.
• Highly preferred: exposure to service mesh technology such as Istio, including mTLS, traffic routing, and observability concepts.
• Highly preferred: familiarity with government delivery compliance frameworks, including RMF, STIGs, FedRAMP, NIST 800-53, and IL4/IL5/IL6 controls.
• Highly preferred: experience supporting air-gapped, disconnected, classified, or resource-constrained deployments.
• Highly preferred: exposure to SBOMs, SCA, SAST, DAST, container scanning, admission control, OPA/Gatekeeper, Kyverno, Sigstore, or similar supply chain security tools.
• Highly preferred: an existing TS/SCI clearance.
• Plus: interest in data platforms, streaming systems, MLOps, and operational AI/ML workloads, and prior exposure to Kafka, Flink, KServe, Kubeflow, or Ray.

Conditions

Hybrid work in HI, with up to 30% travel.

Equal opportunity: all applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Benefits

• Highly competitive salary.
• Fully covered healthcare, dental, and vision coverage.
• 401(k) with company match.
• PTO as needed plus 11 paid holidays.
• Education and training benefits.
• Generous referral bonuses.
• Further benefits are offered, but details are not listed.