Applied AI Engineer

About the role

The owns the design and delivery of AI tools that directly accelerate nuclear engineering workflows. You will partner closely with engineers across simulation, safety analysis, and design to identify bottlenecks and replace manual, legacy processes with intelligent, automated solutions. This role gives you the freedom to redefine how nuclear engineering is done by challenging long-standing assumptions and introducing modern AI-first thinking into every critical path. You will build production-grade tools that let non-specialists run complex analyses and make decisions without waiting for weeks of specialist effort. Success in this role is measured by the speed, reliability, and scalability of the AI systems you ship and the engineering impact they create across the organization. You are expected to communicate clearly with both technical and non-technical stakeholders, translating ambiguous problems into concrete, automatable workflows. This position is embedded in a mission-driven, high-urgency environment where transparency, accountability, and continuous learning are core cultural values.

Key facts

What you'll do

Build AI tooling so that every engineer can run complex safety and physics analyses before design reviews, without waiting on a specialist.

Automate legacy simulation workflows so engineers can run neutronics with a config file instead of learning decades-old codes from scratch.

Integrate with internal tools- tickets, design-tree, file management- and building agents that handle triage, routing, and prioritization automatically.

Partner with domain experts to translate nuclear engineering requirements into well-scoped AI features and experiments.

Prototype end-to-end AI solutions rapidly, validate them against physics and safety constraints, and iterate based on expert feedback.

Own the full lifecycle of AI features from discovery, through implementation, testing, and deployment into production environments.

Establish reusable patterns for data, prompts, model serving, and monitoring that can scale across engineering teams.

Continuously measure the impact of AI tools on engineering throughput, quality, and cycle time, and refine based on evidence.

Contribute to technical documentation, design reviews, and cross-team alignment to ensure AI solutions remain maintainable and auditable.

Act as a bridge between cutting-edge AI techniques and the rigorous requirements of nuclear safety-critical engineering.

Drive adoption of new workflows by training users, gathering feedback, and improving the user experience of AI-assisted tools.

Identify and mitigate risks related to model behavior, data quality, and integration complexity in collaboration with safety and compliance stakeholders.

Requirements

BS or higher in engineering, physics, chemistry, applied math, or related technical field.

Proficiency in Python and software engineering fundamentals.

Experience building tools or workflows using LLMs, AI agents, or modern AI techniques.

Ability to work extended hours and weekends as necessary.

Ability to obtain and maintain U.S. government security clearance, if required for the role.

Eligibility to work in the United States without sponsorship for this role.

U.S. location is required for this position.

You must be able to pass all applicable background checks and meet the security requirements of the role.

Nice to have

Engineer who codes- You studied a hard STEM field: physics, chemistry, mechanical, electrical, nuclear, math. You can follow a technical conversation with a domain expert and know which parts of their workflow are automatable before they do. You write clean, production-grade Python.

Versatile engineering fundamentals- This role requires mastering many different fields quickly: neutronics, integrated safety, data, manufacturing. You don't need to be the expert. You need to get fluent enough, fast enough, to build something useful.

AI fluency- You genuinely enjoy using AI to solve problems - RAG, tool-use architectures. You're constantly thinking about how to apply AI to reinvent or restructure existing workflows.

Ships proactively- You don't wait for a spec, a roadmap, or permission. You see the bottleneck, propose the approach, and show off prototypes before you're asked.

Practical notes

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