Applied AI Engineer – Fusion Systems
About The Position
We are a fusion power company based in Everett, WA, with the mission to build the world's first fusion power plant, enabling a future with unlimited clean electricity. Our vision is a world with clean, reliable, and affordable energy for everyone. Since Helion's founding in 2013, we have raised over $1 billion from long-time investors such as Sam Altman, Mithril, and Capricorn Investment Group as well as new investors SoftBank and Lightspeed to propel us forward. Our last prototype, Trenta, completed 10,000 high-power pulses and reached plasma temperatures of 100 million degrees Celsius (9 keV). We are now operating Polaris, our next prototype on the path to the world's first fusion power plant. This is a pivotal time to join Helion. You will tackle real-world challenges with a team that prizes urgency, rigor, ownership, and a commitment to delivering hard truths – values essential to achieving what no one has before. Together, we will change the future of energy, because the world can't wait. We’re looking for someone to build Helion’s internal knowledge foundation from the ground up—capturing operational procedures, experimental insights, and machine behavior—and turning that into a structured, scalable system that can support AI-assisted workflows and future automation. This role spans documentation, data structuring, and applied AI. You’ll work directly with engineers and operators to turn fragmented, implicit, and fast-changing knowledge into something durable, searchable, and actionable. This is a hands-on, applied role focused on building systems around LLMs and operational data—not training models from scratch.
Requirements
- Experience with data or knowledge modeling (schemas, metadata, ontologies)
- Experience with technical documentation systems (e.g., Confluence/Jira or similar)
- Strong software engineering skills (Python or similar)
- Ability to structure ambiguous information into structured systems
- Experience working with domain experts to extract knowledge
Nice To Haves
- Experience building internal tools for engineering teams
- Exposure to CAD or engineering design tools
- Experience using LLM APIs (e.g., OpenAI, Claude) in production systems
- Experience building LLM-powered tools (RAG, search, etc.)
- Exposure to large scale hardware environment
Responsibilities
- Capture & document procedures, experiments, and workflows by partnering with engineers and operators to turn fragmented knowledge into clear runbooks
- Structure & standardize documentation through docs-as-code practices, including versioning, formatting, reviews, and defined schemas
- Integrate & organize data by linking documentation with logs, configs, and analysis outputs to improve consistency and clarity
- Develop AI-assisted tools by partnering with software engineers to inform LLM-powered solutions
- Prototype automation through lightweight agents and workflows (e.g., run summaries, anomaly investigation) while laying the foundation for more advanced systems
Benefits
- Medical, Dental, and Vision plans for employees and their families
- 31 Days of PTO (21 vacation days and 10 sick days)
- 10 Paid holidays, plus company-wide winter break
- Up to 5% employer 401(k) match
- Short term disability, long term disability, and life insurance
- Paid parental leave and support (up to 16 weeks)
- Annual wellness stipend
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
