СШАApplied AI Engineer, Internal Systems
2 нед. назад
80k–210k USD / годСШАOnsite
aideploymentreliabilitycrm
Develop and maintain AI tools for internal company systems to improve operational efficiency.
О компании
- At , we are rebuilding logistics infrastructure for the national security missions of the United States and allied partners. We build AI systems that determine how logistics decisions are made — not just how they're executed. From factory to foxhole, we operate at the layer where data becomes decisions, and decisions make the advantage.
- The logistics infrastructure that supports America's warfighters and humanitarian disaster responders is overdue for transformation, and we are building it. From defense operations to disaster response, we're solving the hardest problems that keep missions moving when it matters most. Join a team where the mission is the point. Compensation: offers competitive compensation commensurate with experience. Actual compensation may vary based on experience, skills, and location. In addition to base salary, we offer a generous equity grant, full healthcare coverage, 401k, unlimited PTO, and the perks of working in a high-caliber, mission-driven environment.
- This position may require the ability to obtain and maintain a U.S. government security clearance. The successful candidate must be able to work in a classified environment when necessary.
- We comply with the United States Department of Labor's Pay Transparency provision .
- Note: Due to the nature of certain government contracts held by this organization, U.S. citizenship is a requirement for all positions at . Proof of citizenship will be required prior to employment if selected.
Обязанности
- Every hour spent chasing information or moving it between tools is an hour someone can't spend on the work they were hired to do. This role exists to remove that overhead.
- As the Applied AI Engineer, Internal Systems you'll own the engineering behind the AI tools uses to run the company. You'll work alongside the Internal AI Operations Product Manager to shape solutions, with the technical design and implementation in your hands. You'll also own deployment and reliability. Your users will be your colleagues. Work together with them to understand the bottlenecks, connect information across internal tools, and build agents that carry tasks through to completion.
Требования
- You've shipped software people use and maintained it after launch. You can turn an unclear problem into a technical plan and ship a useful first version.
- Strong programming ability in Python or TypeScript, with experience building APIs and working with databases.
- Experience building LLM applications or agents that use external tools and data. You can explain how you tested them and where they fail.
- Enough experience across the stack to build a usable interface and deploy the service behind it.
- Engineering judgment about reliability and security. You know when a model needs a human check and when a simpler implementation will work better.
- Comfort working directly with nontechnical colleagues. You can explain a tradeoff clearly and change your approach when the workflow demands it.
- Experience building internal tools, evaluating AI outputs, or integrating business systems would help.
Другое
- Projects could include an entire coding agent harness, an assistant that answers questions from internal documents with sources and access controls, an agent-native CRM custom to ’s defense business, or an agent that keeps project status current across the systems teams already use. You'll help the product manager scope these projects by assessing technical feasibility and the cost of building and maintaining them.
- You'll own the engineering from first prototype through production:
- Turn workflow problems into technical requirements. Identify where a process should change before automating it.
- Build applications and integrations that connect models to company systems. Use conventional code where the behavior needs to be predictable.
- Turn useful experiments into software people can depend on, with evaluations, observability, and a way to recover when something fails.
- Design access controls and human review into workflows that handle sensitive information or take consequential actions.
- Instrument the systems so we can measure time saved and output quality. Use failure data to improve the software and give the product manager evidence for what to improve or retire.
- Help colleagues use and extend what you build. Document the systems so another engineer can maintain them.
- Work with the Internal AI Operations Product Manager to choose an initial workflow with a team that will use it. Establish a baseline together. Own the technical design and ship a working version with evaluations and observability, then improve it through regular use. By day 90, we should know whether it saves time and meets the team's quality bar, with a plan to keep it working.
- We are building the system that enables faster, smarter logistics decisions in contested environments, and we're doing it with a team of seasoned entrepreneurs, operators, and technologists who have built and scaled solutions in this space before. We hold ourselves to an extremely high standard. We value clear thinking, direct communication, and the kind of ownership that doesn't stop until something actually works.
- Our mission is to create decision advantage when the stakes are the highest. If we succeed, the system doesn't just run; it gets smarter. We're not building AI for its own sake. We're building it because faster, smarter decisions in the most demanding environments on earth can't wait. If you want to work somewhere the stakes are real and the mission is urgent — you'll fit in here.