Software Engineer V, AI Digital & Engineering Software

X-energy LLC conducts a thorough recruiting process and will never issue offers without interview to discuss qualifications and responsibilities. All applications will be submitted via our company career page, www.x-energy.com/careers/. We will never ask you to provide payment information as part of the recruiting process. If anyone claiming to represent X-energy directs you in a manner otherwise, please contact us at www.x-energy.com/contact-us.

Job Description

The AI & Digital Engineering Engineer contributes to X-energy's Artificial Intelligence (AI) Solutions Tiger Team, which accelerates Xe-100 nuclear reactor development workflows by designing and building production-ready, AI-native applications, agentic
workflows, and the platform infrastructure that supports them. Working in a fast-paced, collaborative team environment, this engineer applies modern large language models, agentic AI, and cloud-native engineering to move X-energy from siloed documents toward a living, queryable engineering model spanning requirements, design, manufacturing, regulatory, and deployment processes. This role is essential to Xenergy's mission of becoming an AI-first organization and setting the industry standard for nuclear deployment speed and operational excellence.

 

Job Profile Tasks/Responsibilities:

• Work collaboratively in a tiger-team environment to rapidly develop production-ready AI solutions.
• Leverage Claude Code and AI-assisted development tools to accelerate development, prompt iteration, and maintenance tasks.
• Apply knowledge of LLMs and AI systems to support the platform's AI-native architecture.
• Partner with X-energy's systems-engineering, licensing, and quality-assurance organizations to ensure delivered solutions and AI-generated artifacts meet nuclear-engineering and regulatory expectations.
• Document solutions, architecture decisions, and integration patterns, and support knowledge transfer to relevant technical teams.
• Implement and maintain development best practices and quality standards.
• Execute core tasks and responsibilities with minimal supervision in a fast-paced, team-oriented environment.
• Perform work in accordance with X-energy quality assurance procedures.
• Maintain professional demeanor and behavior at all times in all forms of communication.
• Perform other duties as assigned by manager.

Specialization Tracks

Track A — Front-End & Full-Stack

• Design and implement user interfaces using React, TypeScript, Tailwind CSS, and Vite.
• Develop full-stack solutions connecting front-end interfaces to AWS backend services (Lambda, ECS, DynamoDB, and related services).
• Create responsive dashboards and visualization tools for engineering workflows and AI agent interactions.
• Implement real-time communication through WebSockets and REST APIs.
• Architect maintainable, scalable front-end solutions for technical and engineering applications.
• Implement secure authentication and authorization systems for enterprise applications.
• Create and maintain CI/CD pipelines for web applications.
• Build proof-of-concept demonstrations to validate solution approaches with stakeholders before full development.
• Conduct user acceptance testing to ensure solutions meet real-world engineering requirements, and implement feedback loops between users and developers to iterate rapidly.

Track B — Agentic AI

• Design and implement autonomous agent architectures using AWS Bedrock and related services.
• Develop multi-turn agentic workflows — with reasoning, planning, memory management, and tool calling — optimized for engineering and business contexts.
• Implement RAG and Graph-RAG systems (using Amazon Neptune or equivalent knowledge-graph infrastructure) for enhanced knowledge retrieval, requirements traceability, change-impact analysis, and design reuse.
• Build AI applications for automated requirements extraction and classification, traceability-gap detection, verification-artifact generation, design-review assistance, and cross-discipline consistency checking.
• Develop frameworks with LangChain, LangGraph, and AWS Strands for complex workflows, with safety and alignment controls appropriate for regulated engineering.
• Curate golden datasets and benchmarks evaluating AI outputs against engineering ground truth (e.