Top Senior Linux Jobs in Washington, DC

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio data sources, developing reliable ingestion and processing systems, optimizing data quality, throughput, and cost, and collaborating with AI scientists on training datasets. The role requires ownership of engineering projects, strong backend development, production systems experience, and independent problem-solving in an ambiguous environment.

Build and operate large-scale data pipelines that acquire, process, and optimize audio datasets for AI model training. Responsibilities include discovering data sources, improving data quality, throughput, and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement. The role requires strong backend engineering, production systems experience, and independent problem-solving in a distributed environment.

Build and operate large-scale AI data pipelines, discover audio data sources, optimize data-processing systems for quality, throughput, and cost, and collaborate with AI scientists on training datasets. The role requires backend software engineering, production systems experience, independent problem-solving, and ownership of projects from discovery through continuous improvement. Nice-to-have experience includes web crawling, distributed processing, cloud infrastructure, Terraform, dataset quality, and audio processing.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable ingestion and processing systems, optimizing data quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement in a distributed, ambiguous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering audio data sources, developing reliable data-processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires ownership of engineering projects from discovery through continuous improvement, with emphasis on backend development, production systems, data acquisition, and scalable infrastructure.

Build and operate large-scale data pipelines for AI model training, including discovering audio data sources, optimizing processing systems for quality, throughput, and cost, and collaborating with AI scientists. Own engineering projects from discovery through continuous improvement while working independently in an ambiguous environment.

Build and operate large-scale audio data pipelines for AI model training. Responsibilities include discovering data sources, developing reliable processing systems, optimizing quality, throughput, and cost, and collaborating with AI scientists. The role requires strong backend engineering, production systems experience, Python and Bash proficiency, and independent ownership of projects. Experience with web crawling, distributed processing, GCP, Terraform, machine-learning datasets, or audio processing is advantageous.

Build scalable data pipelines and processing systems for AI model training at petabyte scale. Responsibilities include discovering audio data sources, improving dataset quality and processing efficiency, optimizing throughput and cost, collaborating with AI scientists, and owning engineering projects from discovery through continuous improvement.

Build and operate large-scale audio data pipelines for AI model training. The role involves discovering data sources, optimizing data processing for quality, throughput, and cost, partnering with AI scientists, and owning engineering projects from discovery through continuous improvement.

Owns end-to-end post-sales technical support for federal and special-program customers in secure, classified, and air-gapped environments. Diagnoses issues across Linux, compute, GPUs, networking, storage, cloud, and applications; collects and sanitizes diagnostics; manages escalations; maintains hardened deployments; supports hardware replacement; writes knowledge-base content; and provides customer and pre-sales support. The role includes on-call rotations, secure-facility work, and regional and domestic travel.

Lead the technical direction and architecture of the Foundations platform team, owning authentication, authorization, SSO, secrets management, tenancy, and core platform services. Design APIs, drive services through launch, make technical decisions, establish engineering standards, and mentor engineers without formal management authority. Partner with engineering and product leaders to align execution with priorities.

Design and build data infrastructure automation, observability, health tooling, dashboards, and system improvements for large-scale object storage platforms. Lead technical designs and feature rollouts across services, improve fleet stability and throughput, automate hardware lifecycle processes, and partner with on-call teams to reduce operational toil and incidents.

Designs and manages cloud infrastructure across development, staging, and production using Terraform and AWS. Builds containerized environments with Docker, ECS, and Kubernetes; develops CI/CD pipelines; manages networking, routing, APIs, WAF, monitoring, and autoscaling. Troubleshoots infrastructure and deployment issues, optimizes performance and reliability, and collaborates with development and QA teams. The role also supports cloud-agnostic architecture, observability, Linux administration, and automation scripting.

Develop and maintain enterprise Ansible automation, infrastructure-as-code solutions, REST APIs, scripts, CI/CD pipelines, and integrations across complex infrastructure environments. Manage automation projects through the full software development lifecycle, support production systems, document solutions, troubleshoot issues, and collaborate with infrastructure, security, and service teams. The role requires secure coding, Agile delivery, on-call participation, U.S. citizenship, and eligibility for Public Trust clearance.

Own and evolve production infrastructure for AI workloads, including Kubernetes, cloud-native migrations, scheduling, orchestration, observability, infrastructure as code, deployment workflows, security, reliability, and incident recovery. Partner with engineering and business operations teams to build dependable platform capabilities. The role requires deep production Kubernetes experience, strong cloud and Linux fundamentals, architectural judgment, automation skills, and end-to-end ownership of infrastructure systems.

Design, operate, and evolve production GCP infrastructure, including GKE clusters, networking, IAM, shared services, and Terraform automation. Troubleshoot complex Kubernetes, Linux, networking, DNS, and distributed-systems issues; improve observability, security, scalability, reliability, and cost efficiency. Lead upgrades, migrations, architecture improvements, technical reviews, and mentorship while partnering with Platform Engineering, SRE, and Security teams.

Provide technical leadership for site reliability engineering, applying software engineering practices to large-scale operations. Design automated, repeatable operational solutions; monitor service objectives, application performance, and business metrics; improve resiliency, efficiency, and cost. Support cloud and on-premise infrastructure, production applications, deployment automation, testing, and vulnerability response. Partner with software development, security, and business teams while promoting Agile practices, change management, training, and operational health.

Own and scale multi-cloud infrastructure across AWS, GCP, Cloudflare, and Hetzner. Manage Kubernetes production environments, Terraform infrastructure, observability, monitoring, CI/CD, incident response, networking, security, and cloud cost optimization. Partner with engineering teams on architecture, deployment reliability, developer experience, and AI workload infrastructure. Participate in L2 on-call rotations and lead lasting improvements to infrastructure resilience and performance.

Provides Tier III administration for mission-critical Linux and Windows infrastructure across multiple datacenters. Responsibilities include managing RHEL systems, Windows environments, VMware vSphere, Oracle appliances, DNS, user permissions, repositories, system performance, backups, logs, and Bash automation. The role also supports secure cloud and on-premises platforms, virtualization, containerization, Ansible automation, STIGs, RMF, and DoD cybersecurity standards while partnering with cybersecurity and engineering teams.

Designs, integrates, deploys, and troubleshoots autonomy and vehicle-intelligence systems across embedded hardware and software platforms. Responsibilities include integrating sensors, autopilots, datalinks, PNT/GPS/INS, and ground control stations; supporting UAV flight tests; conducting SIL and HIL validation; collaborating with vendors and defense customers; and delivering customer demonstrations. The role requires strong C++ development, robotics integration, networking, embedded Linux, and eligibility for a U.S. security clearance.

Lead architecture and roadmap for Azure PostgreSQL systems; design and review scalable, maintainable database engine features (query processing, storage, transaction logging, recovery, versioning, IO, scale-out). Influence coding standards and run code reviews, write proof-of-concept or production code, contribute to open-source PostgreSQL/Linux, and participate in rotational on-call operations.

Designs, deploys, tests, certifies, operates, patches, and maintains DevSecOps infrastructure tools and dependencies. Manages Linux servers, infrastructure-as-code deployments, containerized and cluster-based architectures, dynamic website services, monitoring tools, and primary operations and maintenance functions. Uses scripting and programming to troubleshoot interoperability and infrastructure issues while supporting secure, reliable federal mission environments.

Develop and maintain cloud service delivery models and architectures across PaaS, IaaS, SaaS, and DaaS. Implement DevSecOps automation, migrate applications to cloud environments, debug cloud stacks, optimize costs, establish secure cloud environments, and ensure availability. The role requires AWS, Linux, Bash, Terraform or Vault, Kubernetes, DNS, load balancing, and TLS experience, along with an active Top Secret clearance and CI Polygraph eligibility.

Manage Azure cloud infrastructure, including compute, storage, networking, load balancing, DNS, security, monitoring, and logging. Build CI/CD pipelines and secure Linux machine images, implement Infrastructure as Code, troubleshoot deployments, and improve application reliability. This two-month contractor engagement requires independent delivery of production-quality infrastructure, with opportunities to support multi-cloud environments and confidential computing.

Own Anthropic’s endpoint platform, including MDM infrastructure, macOS and mobile configuration as code, patching, zero-touch provisioning, telemetry, compliance controls, and automation. Operate the platform as a production service with observability, incident response, progressive rollouts, and rollback. Partner with Security, developer, and infrastructure teams on endpoint hardening and trusted-device access. Support Linux systems, document platform operations, and provide advanced escalation support.