Software Engineer IV, Artificial Intelligence

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, x-energy.com ↗ . 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 x-energy.com ↗ .

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:

• 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:

• Research and implement cutting-edge techniques in autonomous agent development.

• Implement safety and alignment protocols for autonomous systems in engineering contexts.

• Develop frameworks with LangChain, LangGraph, and AWS Strands for complex workflows.

• Implement RAG and graph-RAG systems for enhanced knowledge retrieval.

• Create systems for agent reasoning, planning, memory management, and tool calling.

• Develop multi-turn agentic workflows optimized for engineering and business contexts.

• Design and implement autonomous agent architectures using AWS Bedrock and related services.

• Data & Systems Integration:

• Strong experience designing and implementing data lakes and ETL processes.

• Deep expertise in AWS data services including Glue, Aurora, DynamoDB, and S3.

• Background in integrating diverse systems and data sources.

• Experience with API design and implementation.

• Proficiency with data modeling and schema design for varied workloads.

• Understanding of data security and governance best practices.

• 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.

• Product Management:

• Develop detailed technical specifications for AI products and solutions.

• Create and maintain product roadmaps aligned with engineering needs.

• Serve as technical liaison between development team and internal customers.

• Define and track product metrics and success criteria.

• Develop product strategy and positioning for AI solutions.

• Create training materials and documentation for users.

• Design go-to-market strategies for internal AI solution adoption.

• Evaluate and select appropriate AWS services for solution architecture.

• Develop AWS cost optimization strategies and resource planning.

• Create integration strategies between AWS services and existing systems.

• Design and document API specifications and technical requirements.

• Create system architecture diagrams and technical documentation.

• Develop technical prototypes and proof-of-concepts using appropriate frameworks.

• Perform technical analysis of competing solutions and technologies.

• Conduct technical reviews and code walkthroughs with engineering teams.

• Implement performance testing methodologies and benchmarking strategies.

• Create technical acceptance criteria for feature development.

• Design data models and database schemas to support product features.

• Develop technical migration plans for system upgrades.

Job Profile Minimum Qualifications

• Bachelor's degree in computer science, artificial intelligence, or related field from an accredited university or college.

• Experience with Git, GitLab, CI/CD, and modern development workflows.

• Proficiency with Jira, Confluence, and AI-enhanced development environments.

• Experience working in collaborative, fast-paced development teams.

• Strong communication skills and ability to explain complex technical concepts.

• Additional qualifications based on assigned area:

• Front-end Development:

• Strong expertise in React, TypeScript, and modern JavaScript development.

• Experience with Vite, Bun, and Tailwind CSS.

• Proficiency in implementing WebSockets and REST APIs.

• Background developing user interfaces for technical or engineering applications.

• Experience with AWS services for web application deployment.

• Agentic AI:

• Deep expertise in modern large language models and agent architectures.

• Experience implementing multi-turn agentic workflows.

• Proficiency with RAG and graph-RAG implementations.

• Experience with LangChain, LangGraph, AWS Strands, or similar frameworks.

• Strong understanding of AWS AI services, particularly AWS Bedrock.

• Background in developing AI systems for practical business applications.

• Data & Systems Integration:

• Strong experience designing and implementing data lakes and ETL processes.

• Deep expertise in AWS data services including Glue, Aurora, DynamoDB, and S3.

• Background in integrating diverse systems and data sources.

• Experience with API design and implementation.

• Proficiency with data modeling and schema design for varied workloads.

• Understanding of data security and governance best practices.

• ML-Ops:

• Background in deploying and monitoring applications in production environments.

• Knowledge of versioning systems for code and dependencies.

• Experience with continuous integration and DevOps tools.

• Understanding of cloud development lifecycle practices.

• Background in testing frameworks for systems.

• Experience with cloud-based monitoring and alerting solutions.

• Proficiency with cloud deployment services and containerization.

• Product Management:

• Experience in technical product management for software or AI products.

• Background creating product roadmaps and specifications.

• Experience serving as technical liaison with customers.

• Knowledge of product metrics definition and tracking.

• Understanding of go-to-market strategy development.

• Experience creating training materials and doc