Top Tech Jobs & Startup Jobs

Manage, administer, support, and enhance cloud environments; automate cloud resource provisioning with Infrastructure-as-Code; troubleshoot complex issues; develop cloud-native solutions; and mentor team members. The role requires AWS, Linux, Bash, Terraform or Vault, Kubernetes, networking, and Top Secret clearance, with preferred experience in CI/CD, containers, DevOps, GitLab, cloud security, Python, Java, and AWS certifications.

Leads IT project delivery for advanced digital solutions supporting investigative, intelligence, and analytical workflows. Coordinates cloud, data, AI/ML, and DevSecOps teams; manages Agile backlogs, sprints, PI planning, roadmaps, milestones, risks, dependencies, budgets, and stakeholder communications. Translates mission needs into technical requirements and execution plans while guiding modernization initiatives, governance alignment, and cross-functional collaboration in secure hybrid and multi-enclave environments.

Develops, manages, and secures cloud-based container platforms. Automates builds, testing, monitoring, infrastructure provisioning, security scanning, and releases across environments. Troubleshoots CI/CD pipelines using Kubernetes, Docker, Jenkins, and public cloud platforms. Supports container orchestration strategy, platform design, DevOps maturity, and secure technology adoption. Requires TS/SCI clearance and substantial DevOps experience.

Maintain application security for business-critical systems by identifying, prioritizing, and remediating vulnerabilities throughout the software development lifecycle. Lead security discussions, advise development teams on secure practices and controls, and perform SAST, DAST, threat modeling, and application security assessments. Use Veracode and Burp Suite, apply OWASP standards, support security pipeline integration, and address emerging threats while meeting federal security and compliance requirements.

Designs, develops, and maintains scalable data warehouses, data lakes, platforms, and ETL/ELT pipelines. Builds batch and streaming workflows, processes structured and unstructured data, optimizes cloud storage and pipeline performance, and implements data governance and lifecycle management. Guides multidisciplinary teams in agile environments while delivering mission-focused data engineering solutions.

Manage, administer, support, and enhance AWS cloud environments. Design and automate cloud resource provisioning using Infrastructure-as-Code tools, support Kubernetes platforms, resolve complex technical issues, and improve automation across technology stacks. Troubleshoot GitLab CI/CD pipelines, apply cloud security principles, mentor team members, and develop enterprise cloud-native solutions with limited direction.

Serve as a technical go-to-market lead for quantum technologies: support customers in labs or agile environments, apply software engineering and AI/data expertise, grow multi-organization collaborations, and define GTM strategies to capture new quantum and AI business opportunities.

Manage, administer, support, and enhance AWS or Azure cloud environments. Resolve complex infrastructure issues, maintain critical systems, monitor security and compliance, and develop innovative cloud solutions. Mentor or supervise technical staff, with opportunities to lead cloud projects. The role requires Windows or Linux administration, Docker and Kubernetes expertise, cloud management experience, a Top Secret clearance, cloud certification, and the ability to obtain Security+ certification shortly after hire.

Design, provision, secure, and support cloud infrastructure and containerized platforms. Build and troubleshoot CI/CD pipelines, automate environment management with Terraform and scripting, manage compute, networking, storage, servers, and virtual machines, and support mission-critical systems across hybrid and multi-enclave environments.

Design and implement enterprise AI architectures, reference designs, integration patterns, governance frameworks, and technical standards. Partner with stakeholders to define requirements, roadmaps, and scalable AI solutions. Guide teams deploying AI models and analytics on AWS while ensuring security, compliance, resilience, and responsible AI adoption. Communicate technical strategies to leadership and nontechnical audiences.