Software Engineer III, AI Digital & Engineering Software

X-energy LLC is an AI-first organization accelerating Xe-100 nuclear reactor development through production-ready, AI-native applications, agentic workflows, and platform infrastructure.

About the role

The AI & Digital Engineering Software Engineer III supports X-energy's Artificial Intelligence (AI) Solutions Tiger Team, designing and building AI-native applications and the platform infrastructure that supports them. This role applies modern large language models, agentic AI, and cloud-native engineering practices to transform siloed documents into a living, queryable engineering model spanning requirements, design, manufacturing, regulatory, and deployment processes. Operating under general supervision with moderate latitude for independent judgment, this engineer contributes to setting the industry standard for nuclear deployment speed and operational excellence.

Responsibilities

• Work collaboratively in a tiger-team environment to 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.
• Perform work in accordance with X-energy quality assurance procedures.
• Maintain professional demeanor and behavior 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.
• Assist in the design of 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.
• Conduct user acceptance testing and support feedback loops between users and developers.

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 — for engineering and business contexts.
• Implement RAG and Graph-RAG systems for enhanced knowledge retrieval, requirements traceability, change-impact analysis, and design reuse.
• Build AI applications for automated requirements extraction, traceability-gap detection, verification-artifact generation, design-review assistance, and cross-discipline consistency checking.
• Develop workflows using LangChain, LangGraph, and AWS Strands for routine and moderately complex use cases, applying safety and alignment controls.
• Assist in curating golden datasets and benchmarks evaluating AI outputs against engineering ground truth.
• Assist with evaluation and safety pipelines using DeepEval, Ragas, or equivalent self-hostable frameworks within the GovCloud boundary.
• Develop MCP (Model Context Protocol) tools that expose engineering systems, reasoning capabilities, and agent workflows to the platform and external AI clients.
• Stay current with emerging techniques in autonomous agent development and escalate opportunities for adoption.

Track C — Data & Systems Integration

• Assist in the design and build of the AWS-native data lakehouse / Common Data Environment using S3, Apache Iceberg, AWS Glue Data Catalog, Lake Formation, and Athena.
• Contribute to the canonical engineering data model spanning Xe-100 requirements, bill-of-materials (BOM), configuration items, test and simulation results, quality records, and digital-thread artifacts.
• Assist with schema governance — data contracts, schema registry, versioning, backward-compatibility rules, and deprecation workflows.
• Implement a tiered data-classification model enforced at the data layer via Lake Formation tag-based access control and row/column-level security.
• Implement data lineage and provenance tracking supporting NQA-1 audit and 10 CFR 50 Appendix B traceability.
• Build Change Data Capture (CDC) and event-driven pipelines that synchronize authoritative systems into the lakehouse.
• Assist with integrations between customer, partner, and supplier engineering systems (Siemens Teamcenter, PTC Windchill, Dassault 3DEXPERIENCE, Aras Innovator, Siemens Polarion, IBM DOORS/DOORS Next, Jama Connect, Oracle Primavera P6, Procore, SAP ERP, Box) and X-energy's platform.
• Parse, normalize, and map specialized engineering data formats including STEP, JT, IFC, ReqIF, SysML v2 XMI, QIF, DWG/RVT, and proprietary PLM exports.
• Assist with identity federation design for external partners and help apply export control and data residency requirements.
• Support definition of API contracts and versioning strategies; monitor cross-organizational data flows, including partner-side connectivity, schema drift, and SLA compliance.
• Support data-quality standards, validation pipelines, and metric dashboards that feed AI agent eval harnesses and NRC submission workflows.

Track D — Platform Infrastructure & DevOps

• Design, build, and maintain containerized applications using Docker, including image building, testing, versioning, and optimization.
• Develop and maintain GitLab CI/CD pipelines, including runner configuration, pipeline optimization, monitoring dashboards, and automated testing workflows.
• Assist with the architecture of AWS infrastructure using Terraform, including ECS, ECR, VPC, EC2, ALB/NLB, and other cloud services.
• Administer and optimize AWS data services including DocumentDB, OpenSearch, Redis, Aurora Postgres, DynamoDB, and S3.
• Implement and maintain monitoring, alerting, and observability solutions using Datadog and CloudWatch.
• Support security and compliance requirements, including ACM certificate management and security best practices.
• Assist with release engineering efforts — versioning strategies, deployment automation, and rollback procedures.
• Create testing frameworks for validating system behavior in serverless environments and configure/optimize container orchestration services.
• Implement versioning and governance for code and dependencies using version control systems.
• Collaborate with development teams to optimize application performance, troubleshoot production issues, and implement infrastructure improvements.
• Participate in on-call rotation to support system reliability and incident response.

Product-Management and Technical-Leadership Activities

Depending on scope and under the guidance of senior engineers, an engineer in this role may:

• Contribute to technical specifications and roadmaps aligned with engineering needs.
• Serve as a technical point of contact between the development team and internal customers on assigned work.
• Help track product metrics and success criteria.
• Support evaluation of appropriate AWS services.
• Produce system architecture diagrams and API documentation.
• Participate in technical reviews and code walkthroughs.
• Develop technical prototypes and proof-of-concepts.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Systems Engineering, Engineering, or a related field from an accredited university or college.
• Typically, five years of relevant software engineering experience, including experience in one or more of the specialization tracks described above.
• Experience with Git, GitLab, CI/CD, and modern development workflows.
• Proficiency with Jira, Confluence, and AI-enhanced development environments (Claude Code or similar AI-assisted development tools).
• Experience working in collaborative, fast-paced development teams.
• Strong written and verbal communication skills, including the ability to explain complex technical concepts to both technical and non-technical audiences.
• Ability to work a hybrid schedule in the Rockville, MD office Tuesday, Wednesday, and Thursday.

Additional Qualifications by Track

Track A — Front-End & Full-Stack

• Basic to working knowledge of React, TypeScript, and modern JavaScript development; familiarity with Vite, Bun, and Tailwind CSS.
• Working knowledge of implementing WebSockets and REST APIs.
• Some background developing user interfaces for technical or engineering applications.
• Familiarity with AWS services for web-application deployment.

Track B — Agentic AI

• Basic to working knowledge of modern large language models, agentic architectures, and multi-turn agent workflows.
• Some hands-on exposure to at least one of AWS Bedrock, AWS Strands, LangChain, LangGraph, or LlamaIndex.
• Familiarity with RAG and Graph-RAG, including vector search and hybrid retrieval.

Track C — Data & Systems Integration

Meet the general requirements and demonstrate relevant experience in data integration, schema governance, or engineering data formats.

Track D — Platform Infrastructure & DevOps

Meet the general requirements and demonstrate relevant experience in containerization, CI/CD, or cloud infrastructure.