Senior Applied AI Engineer Software

Senior Applied AI Engineer

Location: Los Angeles, California, United States

Compensation: $139, USD / year

Job Tags: Software

Turning Space into a Transportation Layer for Earth

Inversion builds advanced reentry systems to deliver next‑generation capabilities from space. Our mission is to make Earth radically more accessible by turning Low‑Earth Orbit into an on‑demand logistics domain. We see space not as a destination, but as a platform — one that unlocks unprecedented speed and global reach. Our spacecraft are designed to deliver payloads anywhere on Earth in under an hour, operating through extreme reentry conditions and landing with high precision.

These systems open the door to new ways of testing, delivering, and operating at hypersonic speeds. Inherently dual‑use, our technology is built to meet urgent national security needs while laying the groundwork for future commercial applications. Backed by leading investors including Y Combinator, Spark Capital, and Lockheed Martin Ventures, and working with partners such as the U.S. Space Force and NASA, Inversion is pushing the boundaries of what’s possible in space‑based defense and logistics.

As a Senior Applied AI Engineer at Inversion, you will define and build the company’s internal AI tooling strategy from the ground up. You will own the research, development, deployment, and iteration of AI systems that help teams across the company work faster and make better decisions, beginning with software engineering workflows and expanding to broader company‑wide use cases. This role is cross‑functional and ambiguous by design: you will identify high‑leverage opportunities, prototype quickly, harden what works, and help shape what AI‑enabled work should look like  will be a key member of the Internal Software Tools team, reporting directly to the Director of Software.

• Design, build, and deploy internal AI systems and agent‑based workflows that unlock useful AI capabilities for teams across the company.
• Own the end‑to‑end lifecycle of applied AI tools, including problem definition, prototyping, evaluation, deployment, monitoring, iteration, and long‑term maintenance.
• Develop agent platforms and supporting infrastructure that can safely and reliably perform tasks such as information retrieval, document analysis, workflow automation, and software development assistance.
• Research and validate technical approaches for internal knowledge access and agent behavior, including retrieval‑augmented generation, tool use, prompt architecture, and model evaluation methods.
• Establish best practices for applied AI development at Inversion, including experimentation, evaluation, rollout strategy, observability, and responsible use of AI systems.
• Help define the long‑term product and technical vision for how AI tools should be used across the company as Inversion’s first AI‑focused engineer.

• Direct experience building and deploying applied AI or LLM‑powered systems in production or near‑production environments.
• Experience working with modern LLM application patterns such as tool use, prompt design, structured outputs, agent workflows, or retrieval‑based systems.
• Strong software engineering fundamentals, including system design, testing, debugging, code quality, and maintainability.
• Experience developing backend systems, APIs, internal tools, or automation frameworks.
• 5+ years of professional software engineering experience building and shipping production‑quality software systems.
• An innovative and optimistic approach to an environment with high ambiguity, shifting priorities, and loosely defined problem spaces.
• Position may require occasional extended hours and/or weekend work.

• Experience building internal AI assistants, coding agents, workflow automation systems, or knowledge assistants for enterprise or technical teams.
• Experience designing retrieval systems over large internal document sets, including search, indexing, chunking, ranking, metadata strategies, or RAG‑style architectures.
• Experience with fine‑tuning, model experimentation, or other techniques for adapting foundation…