Software Engineer III, Artificial Intelligence

X-energy•Rockville, MD

1d•Hybrid

About The Position

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.

Requirements

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.
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.
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.
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.
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.
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 documentation.
Familiarity with AWS service portfolio and selection strategies.
Experience with AWS solution architecture and cloud cost management.
Background in AWS integration planning for enterprise applications.
Proficiency in technical writing and API documentation.
Experience with system architecture design and diagramming tools.
Background in software development or programming.
Knowledge of database design and data modeling principles.
Experience creating technical prototypes or proof-of-concepts.
Understanding of software testing methodologies and performance benchmarking.
Background in system integration and technical requirements gathering.
Experience with technical acceptance testing and validation.
Typically, five years of experience in a relevant role required.

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.
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.
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.
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.
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.
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.