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Associate Engineer - Data Platform

Defense Unicorns
CompanyDefense Unicorns
CategoryEngineering
LocationRemote
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted15 Jun 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
Role Description Defense Unicorns is seeking an Associate Engineer who is energized by learning, ready to get their hands dirty, and genuinely motivated by knowing that software actually works — not just that it deploys. This is a role for someone early in their career who wants to grow quickly in a rigorous technical environment and contribute to systems that matter. You will own real work from day one: packaging and deploying open source software, writing test suites that give the team confidence to ship, and building the tooling and documentation that make complex distributed systems understandable and demonstrable. You will work directly with other engineers and product leaders who will invest in your growth. If you find satisfaction in breaking things on purpose, documenting what you find, and making sure the next person can reproduce it — this role is a strong fit. Responsibilities Write and maintain test suites — integration, end-to-end, and regression — that give the team confidence to ship Write automated tests and test documentation that any engineer can reproduce and act on Package and deploy open source software components in Kubernetes environments Build and maintain seed data tooling and scripts that make the platform demonstrable from scratch Contribute to internal tooling, dashboards, and documentation Write clear bug reports and reproduction steps that the team can act on immediately Participate actively in code review, seeking feedback, and growing your technical judgment   Travel Expectations/Requirements Travel: 10-20%, primarily for customer engagements and company gatherings.   What You'll Work On Test suites and validation tooling that give the team confidence to ship a new capability Deployment automation and tooling that let any engineer stand up the full platform from scratch Real bug reports and edge case documentation that directly accelerate how quickly other engineers can identify and resolve issues Runbooks and demo scripts that make a complex distributed system legible to anyone picking it up for the first time Required Qualifications Degree in Computer Science, Electrical Engineering, Aerospace Engineering, or a related technical field — or equivalent demonstrated hands-on technical ability Active and effective user of AI-assisted development tools (GitHub Copilot, Claude, Cursor, or similar) — you know how to prompt well, validate output, and catch when the model is wrong An orientation toward testing and validation — you find satisfaction in knowing that something works, not just that it runs; you break things intentionally and document what you find U.S. citizenship and the ability to obtain a security clearance Preferred Experience and Qualifications Comfort with at least one programming language — Python, Go, TypeScript, or similar; willingness to learn what the stack requires Genuine curiosity about how distributed systems work and fail — you want to understand the system, not just run scripts against it Comfort with command-line tooling and Linux environments Ability to write clearly: bug reports, documentation, and runbooks that another engineer can follow Comfortable working asynchronously in a remote environment ✨🦄   Amazing To Haves Any exposure to Kubernetes — even running a local cluster (k3s, k0s, minikube) counts Familiarity with containerization (Docker, container images) Experience with any database — relational (Postgres, MySQL), document (MongoDB), key-value (Redis), or similar Coursework or personal projects involving data, AI, or machine learning Interest in defense, national security software, or government technology Contributions to open source projects, even small ones   Don't have all the preferred experience or qualifications? Studies show that underrepresented groups like women and people of color are less lik
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