Senior DevOps Engineer

Residency

All applicants must currently reside in the United States

Overview

Join BigBear.ai to design, operate, and secure container platforms that directly enable Defense Intelligence Agency (DIA) mission outcomes. You’ll lead the engineering and operational work to provide a resilient, compliant, and scalable container environment advancing how analysts and developers deliver capabilities in a secure, cloud-enabled world.

What you will do

Lead design, build, and operation of container platforms (Kubernetes, container runtimes, orchestration tooling) that meet security and operational requirements for classified environments.

Drive DevOps/DevSecOps maturity: automate builds, testing, deployments, observability, and release processes across multiple environments.

Lead CI/CD pipeline development and troubleshooting—identify root causes, remove bottlenecks, and improve pipeline reliability and speed.

Implement and enforce secure configuration, policy-as-code, and runtime security controls for container workloads.

Advise architecture and platform strategy—recommend technology choices, capacity planning, and operational procedures that leverage cloud capabilities (AWS/Azure) while satisfying DIAs security constraints.

Own IT change-management processes and ensure changes are auditable, tested, and follow governance requirements.

Mentor engineers, establish runbooks/playbooks, and lead incident response and postmortems to minimize production impact.

Collaborate with cross-functional teams (platform, network, security, SRE, and application owners) to integrate containerized applications safely into the enterprise landscape.

What you need to have

TS/SCI clearance with current CI polygraph (required).

Bachelor’s degree + 10+ years of professional DevOps experience, or Master’s degree + 8+ years of experience.

Minimum 3 years of documented IT change management experience (mandatory).

8+ years building tooling and processes that advance DevOps/DevSecOps maturity through automation (builds, regression testing, monitoring, automated releases).

8+ years diagnosing and resolving CI/CD pipeline failures, performance issues, and operational slowness.

Proven experience developing, managing, and securing containerized solutions (Kubernetes, Docker, or similar).

Experience developing enterprise cloud-native solutions in public cloud providers (AWS and/or Azure).

Experience mentoring or supervising team members in engineering or operations roles.

Strong scripting skills (Python, Bash/shell) and experience with configuration management, IaC, and pipeline tooling (Jenkins, GitLab CI/CD, or comparable).

What we'd like you to have

Deep Kubernetes platform engineering experience (operators, CRDs, Operators Framework, Helm, Kustomize).

Experience with service mesh (Istio/Linkerd), runtime security (Falco, Aqua, Prisma Cloud), and policy engines (OPA/Gatekeeper).

Familiarity with container registry hardening, image scanning, SBOMs, and supply-chain protections.

Experience with observability stacks (Prometheus/Grafana, ELK/Opensearch) and distributed tracing.

Prior experience delivering platforms in constrained/secure environments (SCIF or classified deployments).

Experience with cloud native CI/CD patterns (GitOps, ArgoCD) and advanced automation across stacks.

IT program management experience, strong oral and written communication skills.

Pay transparency

Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered.

About BigBear.ai

BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai.

BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.

Lead design, build, and operation of container platforms (Kubernetes, container runtimes, orchestration tooling) that meet security and operational requirements for classified environments.

Drive DevOps/DevSecOps maturity: automate builds, testing, deployments, observability, and release processes across multiple environments.

Lead CI/CD pipeline development and troubleshooting—identify root causes, remove bottlenecks, and improve pipeline reliability and speed.

Implement and enforce secure configuration, policy-as-code, and runtime security controls for container workloads.

Advise architecture and platform strategy—recommend technology choices, capacity planning, and operational procedures that leverage cloud capabilities (AWS/Azure) while satisfying DIAs security constraints.

Own IT change-management processes and ensure changes are auditable, tested, and follow governance requirements.

Mentor engineers, establish runbooks/playbooks, and lead incident response and postmortems to minimize production impact.

Collaborate with cross-functional teams (platform, network, security, SRE, and application owners) to integrate containerized applications safely into the enterprise landscape.

TS/SCI clearance with current CI polygraph (required).

Bachelor’s degree + 10+ years of professional DevOps experience, or Master’s degree + 8+ years of experience.

Minimum 3 years of documented IT change management experience (mandatory).

8+ years building tooling and processes that advance DevOps/DevSecOps maturity through automation (builds, regression testing, monitoring, automated releases).

8+ years diagnosing and resolving CI/CD pipeline failures, performance issues, and operational slowness.

Proven experience developing, managing, and securing containerized solutions (Kubernetes, Docker, or similar).

Experience developing enterprise cloud-native solutions in public cloud providers (AWS and/or Azure).

Experience mentoring or supervising team members in engineering or operations roles.

Strong scripting skills (Python, Bash/shell) and experience with configuration management, IaC, and pipeline tooling (Jenkins, GitLab CI/CD, or comparable).