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    REMOTEFULLTIME

    Senior/Staff Software Engineer, DevOps

    TurbineOne logo

    TurbineOne

    Remote · remote · Posted 68d ago

    Sourced fromGreenhouse
    Not disclosed4–8 yrsfulltimeRemote

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    Section · 01

    About this role

    Senior/Staff Software Engineer, DevOps

    Location: Remote (Home Office Anywhere in the United States) Travel: Approximately 2–4 times per year

    About TurbineOne

    TurbineOne is the frontline perception company , delivering decision advantage, enhanced situational awareness, and stronger force protection for those operating in complex environments.

    Our customers rely on us to automate the right parts of the military intelligence cycle while keeping humans in the loop where it matters most. We're a fast-moving, high-performance startup backed by leading DefenseTech investors, building technology that directly impacts mission success.

    If you're excited by difficult engineering problems, ownership, and building systems that operate at the edge, we'd love to talk.

    The Role

    At TurbineOne, DevOps is a software engineering discipline.

    Our team builds the automation, platforms, and internal systems that enable engineers to build, test, release, and operate software deployed on edge hardware around the world.

    One of our highest priorities is expanding our automated testing infrastructure for remotely accessible edge devices. This role will take significant ownership of that initiative while contributing broadly across our DevOps roadmap.

    We're looking for experienced engineers from backgrounds including:

    Site Reliability Engineering (SRE)

    Production Engineering

    CI/CD Engineering

    Build & Release Engineering

    Developer Infrastructure

    Platform Engineering

    Test Infrastructure

    If you've built internal platforms that enable other engineers to move faster, you'll likely be a strong fit.

    What You'll Do

    Design, implement, and operate production-quality infrastructure with significant autonomy.

    Build automated testing infrastructure for software running across heterogeneous edge hardware.

    Make tests reproducible and failures easy to diagnose across diverse hardware platforms.

    Enable Product Engineering and QA teams to contribute automated tests while DevOps owns and evolves the automation platform.

    Improve CI/CD pipelines, build and release systems, deployment automation, developer tooling, and platform reliability.

    Identify high-leverage engineering opportunities, define technical approaches, write production software, and drive major initiatives from ambiguity to successful operation.

    Partner closely with engineering teams to improve developer productivity and software quality.

    What We're Looking For

    Required Qualifications

    Demonstrated Senior- or Staff-level impact designing, building, and owning software systems. We value scope, ownership, and technical leadership over a specific number of years.

    Strong programming ability in at least one production language, with the ability to work comfortably across languages and technology stacks.

    Python and Bash are commonly used in our automation.

    Our product stack is primarily Go and TypeScript.

    Experience in one or more infrastructure-focused disciplines, including:

    Site Reliability Engineering (SRE)

    Production Engineering

    CI/CD

    Build & Release

    Developer Infrastructure

    Platform Engineering

    Test Infrastructure

    Strong experience with Linux, containers, networking, software delivery pipelines, and operational troubleshooting.

    Practical experience designing or supporting automated testing at the unit, integration, end-to-end, or system level.

    Proven ability to navigate ambiguity, make sound technical tradeoffs, collaborate across teams, and deliver results with minimal oversight.

    Bonus Points

    Experience in any of the following areas is especially valuable:

    Hardware-in-the-loop (HIL) testing

    Test infrastructure platforms

    Remote device fleet orchestration

    Edge or embedded systems

    Performance testing

    Chaos engineering

    Internal platform observability

    Distributed systems operating at scale

    Compensation

    We believe exceptional talent should be rewarded competitively.

    The base salary range for this position is $240,000–$280,000 annually. Final compensation will be determined based on several factors, including experience, technical expertise, demonstrated impact, geographic location, and overall alignment with the role.

    In addition to base salary, this position is eligible for equity participation and a comprehensive benefits package.

    Our Culture

    We're a small, fully remote team where ownership matters.

    Success at TurbineOne means being comfortable with:

    Taking initiative without waiting for direction.

    Moving quickly while maintaining engineering quality.

    Communicating openly and collaborating across teams.

    Sharing failures, learning rapidly, and continuously improving.

    Embracing ambiguity and solving hard problems.

    Building what needs to exist rather than waiting for someone else to build it.

    We believe exceptional teams are built on trust, autonomy, accountability, and a willingness to tackle difficult problems together.

    Eligibility

    Applicants must be eligible to obtain a U.S. Government security clearance.

    Sourced from greenhouse

    Section · 02

    Skills

    DevopsBashroadmapPythonTypescriptLinuxCi/Cd

    Section · Company

    About TurbineOne

    TurbineOne logo

    TurbineOne

    San Francisco

    US

    About

    TurbineOne is the frontline perception company that uses ML for real-time threat detection, target recognition, and sensor fusion. TurbineOne is the frontline perception company. It started with the vision of a world where people could sense every threat, speak any language, and deploy robots to dangerous environments instead of putting people unnecessarily in harm's way.

    Industries

    Artificial Intelligence (AI)Machine LearningMobile AppsNational SecuritySecurity

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