Software Engineer III, Artificial Intelligence

About this role

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: • 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.

• 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

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