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Build and document Python automation, support CI/CD pipelines, containerization, data workflows, testing, and JIRA processes for development, QA, and operations teams. Support engineering workflows on NIPR systems, prepare artifacts for potential SIPR migration, and collaborate with cross-functional teams to improve deployment reliability and traceability.
All applicants must currently reside in the United States
At BigBear.ai our team supports mission-focused software development, data operations, and DevSecOps practices across DoD environments. We integrate modern engineering tools, cloud platforms, automated pipelines, and collaborative workflows to enhance system reliability, enable secure deployments, and optimize development and testing operations across NIPR and SIPR enclaves.
The DevOps Engineer will support software development, QA, and operations teams by building and maintaining automation scripts, supporting CI/CD workflows, managing data pipelines, and improving JIRA-based team processes on NIPR systems.
This role is designed for a technically strong early-career engineer with a background in Python, Linux, data workflows, and reproducible computational projects who is motivated to grow into a full DevOps skillset including containerization, orchestration, CI/CD, and cloud deployments.
A structured progression path is provided to advance from Junior to Mid-level responsibilities through hands-on work, mentorship, and exposure to Kubernetes, GitLab CI/CD, AWS, .NET application environments, Databricks, and mission operational workflows.
DevOps & Automation Support
Develop, maintain, and document Python-based automation scripts to support QA, development, and operations teams.
Assist with CI/CD pipeline operations in GitLab/GitHub, including build automation, pipeline testing, and deployment workflows.
Support containerization tasks using Docker and assist with Kubernetes-based application environments as skills develop.
Help maintain version control branches, merge processes, and repository structure for development teams.
Data, Testing & QA Support
Support data handling, SQL-based querying, and structured data preparation for development, QA, and operational analysis workflows.
Assist with Databricks and AWS-based data workflows (training and onboarding provided).
Contribute to testing activities including functional testing, regression testing, defect logging, and pipeline validation.
Optimize JIRA workflows, dashboards, ticket structures, and sprint boards to improve operational efficiency.
Operations & NIPR/SIPR Support
Work on NIPR systems supporting developers, testers, and ops teams; assist with preparing artifacts and documentation for eventual SIPR migration.
Participate in building repeatable processes that improve deployments, environment stability, and traceability.
Progress toward SIPR access and elevated responsibilities as clearance adjudication allows.
Collaboration & Agile Support
Collaborate with developers, QA analysts, product owners, and operations engineers to streamline delivery workflows.
Assist with backlog refinement, user story preparation, acceptance criteria gathering, and sprint execution activities.
Document processes, results, and improvements clearly and consistently.
Education (per labor category)
Bachelor’s degree and 0-2 years of relevant experience; OR
Master’s degree and 0–3 years; OR
8–10 years without a degree.
Technical Skills
Proficiency in Python for automation, data workflows, or computational scripting.
Working knowledge of Linux environments.
Familiarity with Git, GitHub or GitLab workflows.
Basic understanding of SQL, RDS, and DataBricks.
Exposure to Docker or containerized compute environments.
Strong analytical problem-solving skills; ability to debug technical workflows.
Ability to document technical steps and collaborate in an Agile/Scrum environment.
Security Eligibility
Must be able to work on NIPR systems.
Eligibility to obtain a SECRET clearance highly preferred.
Exposure to Kubernetes concepts or container orchestration.
Experience with GitLab CI/CD or GitHub Actions.
Familiarity with AWS services or cloud compute patterns.
Exposure to Databricks, Spark, or distributed data workflows.
Basic understanding of .NET/angular codebases or enterprise applications.
Experience with scientific computing, HPC workflows, or reproducible pipelines.
Familiarity with JIRA administration, workflow optimization, or dashboard customization.
Exposure to MLOps or ML pipeline development (nice-to-have, not required).
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.
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.
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