Vast is developing next-generation space stations and space infrastructure using an incremental, hardware-rich, and capital-efficient approach. Vast is rapidly developing its multi-module Haven Station to support a continuous human presence in space for America and its allies, enabling advanced microgravity research and manufacturing, and supporting a growing space economy for government, corporate, and private customers. Haven Demo’s 2025 success made Vast the only operational commercial space station company to design, build, and operate its own spacecraft in orbit. Next, Haven-1 is targeted to become the world’s first commercial space station, with launch anticipated in 2027, followed by additional Haven modules. Additionally, the company recently announced two new offerings leveraging its space station components and the heritage of Haven Demo: Vast Satellite, a high-power satellite product line; and Vast Lunar Systems, power, communications, and habitats for the Moon.

Headquartered in Long Beach, California, and with more than 1,000 employees and over a billion dollars in private capital, Vast has built the facilities capable of manufacturing America’s next space station. The company plans to develop future habitats and systems for Mars, dedicated modules for government partners, and other crewed systems designed to unlock the expanding long-term space economy.

Vast is looking for a Staff Software Engineer, AI Tooling reporting to the Senior Manager, Software Engineering to support the development of the systems that will be required for the design and build of artificial-gravity human-rated space stations.

This will be a full-time, exempt position located in our Long Beach location.

Responsibilities

Define the technical direction and long-term roadmap for Vast's internal AI platforms and tooling
Architect and lead the development of full-stack AI applications that serve diverse use-cases across the company
Establish engineering best practices, design patterns, and quality standards for AI systems development
Build and maintain production-grade integrations connecting AI models with internal tools, data sources, and workflows
Design and implement pipelines for AI response enforcement, content safety, and output formatting
Drive the evaluation and adoption of emerging AI frameworks, models, and patterns to continuously improve internal tooling
Collaborate cross-functionally with IT Infrastructure, security, and business stakeholders to integrate AI tooling with existing systems
Mentor and guide other engineers contributing to AI initiatives, fostering a culture of technical excellence
Ensure the reliability, observability, and scalability of production AI systems
Rapidly iterate on AI tooling as the technology landscape and company needs evolve

Minimum Qualifications

Bachelor's degree in computer science, math, an engineering discipline, or equivalent work experience
8+ years of software development or relevant industry experience
Proven track record of leading technical initiatives from concept through production deployment
Strong full-stack development proficiency with experience across both frontend and backend systems
Deep understanding of AI/ML concepts, large language model architectures, prompt engineering, and modern AI tooling patterns
Demonstrated experience implementing and maintaining production applications at scale
Experience establishing engineering best practices and providing technical mentorship
Strong cross-functional communication skills with the ability to translate technical concepts for diverse audiences

Preferred Skills & Experience

Experience with Python and TypeScript in production environments
Experience with Svelte or SvelteKit
Experience with OpenWebUI or similar open-source AI interface platforms
Experience building or integrating MCP (Model Context Protocol) servers and gateways
Experience with LLM API integration and AI pipeline development
Experience with containerization and deployment (Docker, Kubernetes)
Familiarity with RAG (Retrieval-Augmented Generation) patterns and vector databases