{"id":3484710,"url":"https://alion.io/job/bigbear-ai-senior-devops-engineer","title":"Senior DevOps Engineer","company":{"id":34812,"name":"BigBear.ai","domain":"bigbear.ai","url":"https://alion.io/company/bigbear-ai-holdings-inc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"iCIMS","truth_index":{"grade":"A","score":100,"open_postings":5,"ghost_share":0,"stale_share":0.2,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-31T05:58:55Z"}},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Washington, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":116000,"max_usd":221000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1808},"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ArgoCD","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Docker","optional":false},{"name":"Falco","optional":false},{"name":"GitLab CI","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Istio","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Kustomize","optional":false},{"name":"Linkerd","optional":false},{"name":"OpenSearch","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Prisma Cloud","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Service Mesh","optional":false}],"status":"live","first_seen_at":"2026-10-29T21:23:57Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-31T18:49:55Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Overview\nJoin 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.\nWhat you will do\nLead design, build, and operation of container platforms (Kubernetes, container runtimes, orchestration tooling) that meet security and operational requirements for classified environments.\nDrive DevOps/DevSecOps maturity: automate builds, testing, deployments, observability, and release processes across multiple environments.\nLead CI/CD pipeline development and troubleshooting-identify root causes, remove bottlenecks, and improve pipeline reliability and speed.\nImplement and enforce secure configuration, policy-as-code, and runtime security controls for container workloads.\nAdvise architecture and platform strategy-recommend technology choices, capacity planning, and operational procedures that leverage cloud capabilities (AWS/Azure) while satisfying DIAs security constraints.\nOwn IT change-management processes and ensure changes are auditable, tested, and follow governance requirements.\nMentor engineers, establish runbooks/playbooks, and lead incident response and postmortems to minimize production impact.\nCollaborate with cross-functional teams (platform, network, security, SRE, and application owners) to integrate containerized applications safely into the enterprise landscape.\nWhat you should have\n TS/SCI clearance with current CI polygraph (required).\nBachelor’s degree + 10+ years of professional DevOps experience, or Master’s degree + 8+ years of experience.\nMinimum 3 years of documented IT change management experience (mandatory).\n8+ years building tooling and processes that advance DevOps/DevSecOps maturity through automation (builds, regression testing, monitoring, automated releases).\n8+ years diagnosing and resolving CI/CD pipeline failures, performance issues, and operational slowness.\nProven experience developing, managing, and securing containerized solutions (Kubernetes, Docker, or similar).\nExperience developing enterprise cloud-native solutions in public cloud providers (AWS and/or Azure).\nExperience mentoring or supervising team members in engineering or operations roles.\nStrong scripting skills (Python, Bash/shell) and experience with configuration management, IaC, and pipeline tooling (Jenkins, GitLab CI/CD, or comparable).\nWhat we'd like you to have\nDeep Kubernetes platform engineering experience (operators, CRDs, Operators Framework, Helm, Kustomize).\nExperience with service mesh (Istio/Linkerd), runtime security (Falco, Aqua, Prisma Cloud), and policy engines (OPA/Gatekeeper).\nFamiliarity with container registry hardening, image scanning, SBOMs, and supply-chain protections.\nExperience with observability stacks (Prometheus/Grafana, ELK/Opensearch) and distributed tracing.\nPrior experience delivering platforms in constrained/secure environments (SCIF or classified deployments).\nExperience with cloud native CI/CD patterns (GitOps, ArgoCD) and advanced automation across stacks.\nIT program management experience, strong oral and written communication skills.\nAbout BigBear.ai\nBigBear.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. 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