Front End Visualization / AI Software Engineer

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

This role is responsible for contributing to X-energy's Artificial Intelligence (AI) Solutions Tiger Team that accelerates XE-100 nuclear reactor development workflows across business and engineering functions. Working under the leadership of the Artificial Intelligence function in a collaborative tiger team environment, this position requires expertise in at least one of the following areas: front-end development, agentic AI, data/systems integration, ML-Ops, or product management. The position will work closely with colleagues to rapidly develop and deploy AI solutions that enhance engineering productivity, knowledge management, and decision support across X-energy.

 

Job Profile Tasks/Responsibilities:

• Work collaboratively in a tiger team environment to rapidly develop production-ready AI solutions.
• Contribute to the design and implementation of autonomous AI systems that enhance XE-100 reactor development.
• Document solutions and support knowledge transfer to relevant technical teams.
• Implement and maintain development best practices and quality standards.
• 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.
• Perform additional duties based on area of assignment:
• Must have experience in two or more of the following areas below:
  • Front-end Development:
    • Design and implement user interfaces using React, TypeScript, Tailwind CSS, and Vite.
    • Develop full-stack solutions connecting frontend interfaces to AWS backend 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 frontend solutions for technical applications.
    • Implement secure authentication and authorization systems for enterprise applications.
    • Create and maintain CI/CD pipelines for web applications.
  • Agentic AI:
    • Design and implement autonomous agent architectures using AWS Bedrock and related services.
    • Develop multi-turn agentic workflows optimized for engineering and business contexts.
    • Create systems for agent reasoning, planning, memory management, and tool calling.
    • Implement RAG and graph-RAG systems for enhanced knowledge retrieval.
    • Develop frameworks with LangChain, LangGraph, and AWS Strands for complex workflows.
    • Implement safety and alignment protocols for autonomous systems in engineering contexts.
    • Research and implement cutting-edge techniques in autonomous agent development.
  • Data & Systems Integration:
    • Design and implement AWS-based data lakes supporting AI workloads.
    • Develop ETL workflows using AWS Glue, Aurora, DynamoDB and related services.
    • Create data pipelines connecting engineering and business systems to AI platforms.
    • Design schemas and data models optimized for AI applications and agent access.
    • Create integration frameworks between different engineering platforms and data models.
    • Implement data warehousing solutions to support business intelligence.
    • Develop secure access patterns for sensitive engineering and corporate data.
  • ML - Ops:
    • Create automated deployment pipelines using modern CI/CD tools.
    • Develop monitoring systems for application performance and reliability.
    • Implement versioning and governance for code and dependencies using version control systems.
    • Design and maintain continuous integration workflows.
    • Establish cloud development lifecycle practices across platforms.
    • Create testing frameworks for validating system behavior in serverless environments.
    • Configure and optimize container orchestration services for application deployment.