Software Engineer 4 - AI & Digital Engineering
$180k - $205k+ 401(k) Match
Expert
Bachelor's
Rockville, MD, USA
HybridThree days in the Rockville office each week.
Software EngineeringAI Application Engineering, Full-Stack Engineering
About the job
Requirements
- A bachelor's degree in Computer Science, Artificial Intelligence, Systems Engineering, Engineering, or a related field from an accredited university or college is required.
- Typically, ten years of relevant software engineering experience is required, including experience in one or more specialization tracks.
- Experience with Git, GitLab, CI/CD, and modern development workflows is required.
- Proficiency with Jira, Confluence, and AI-enhanced development environments such as Claude Code or similar tools is required.
- Ability to work a hybrid schedule in the Rockville, Maryland office Tuesday, Wednesday, and Thursday is required.
- For Track A, working knowledge of React, TypeScript, and modern JavaScript development is required; experience with Vite, Bun, and Tailwind CSS is required.
- For Track A, proficiency implementing WebSockets and REST APIs is required.
- For Track A, a background developing user interfaces for technical or engineering applications is required.
- For Track A, experience with AWS services for web-application deployment is required.
- For Track B, working knowledge of modern large language models, agentic architectures, and multi-turn agent workflows is required.
- For Track B, hands-on experience with at least one of AWS Bedrock, AWS Strands, LangChain, LangGraph, or LlamaIndex is required.
- For Track B, working knowledge of RAG and Graph-RAG, including vector search, hybrid retrieval, re-ranking, and chunking, is required.
- For Track B, proficiency in TypeScript and Python and familiarity with Node.js/Express and a Python web framework such as FastAPI are required.
- For Track B, familiarity with AI evaluation methodology, including golden datasets, LLM-as-judge, red-teaming, and hallucination detection, and exposure to evaluation pipelines using DeepEval, Ragas, Arize Phoenix, or equivalent self-hostable frameworks are required.
- For Track B, working understanding of AWS AI services, particularly AWS Bedrock, is required.
- For Track C, experience designing and implementing data lakes or lakehouses and ETL processes, and working knowledge of AWS data services including S3, Glue, Lake Formation, Athena, Aurora, and DynamoDB, are required.
- For Track C, working experience with at least one open table format, such as Apache Iceberg, Delta Lake, or Apache Hudi, including exposure to schema and partition evolution, is required.
- For Track C, experience designing canonical data models in a regulated or engineering-heavy domain, with exposure to schema governance, data contracts, and multi-producer/multi-consumer patterns, is required.
- For Track C, experience building production ETL pipelines and connectors with schema evolution, error recovery, and observability is required.
- For Track C, hands-on experience integrating at least one enterprise engineering system, such as PLM, requirements management, ERP, or MES, with a data platform is required.
- For Track C, familiarity with identity federation and B2B authentication, including SAML, OIDC, SCIM, and cross-account IAM, and familiarity with engineering data-interchange formats such as STEP, ReqIF, or SysML XMI, are required.
- For Track C, working understanding of data security, classification, lineage, and governance best practices is required.
- For Track D, hands-on experience with Docker containerization, including building, testing, and deploying production applications, is required.
- For Track D, experience administering GitLab CI/CD systems, including runner setup, pipeline configuration, and troubleshooting, is required.
- For Track D, working proficiency with AWS, particularly ECS, ECR, VPC, and Terraform infrastructure-as-code, and experience managing AWS data services such as DocumentDB, OpenSearch, Redis, Aurora Postgres, or DynamoDB, are required.
- For Track D, experience with release engineering and deployment automation is required.
- For Track D, knowledge of monitoring and observability tools and cloud-based alerting solutions is required.
- For Track D, proficiency with Linux and/or macOS command-line environments and container orchestration services is required.
Responsibilities
- Work collaboratively in a tiger-team environment to develop production-ready AI solutions.
- Use Claude Code and AI-assisted development tools to accelerate development, prompt iteration, and maintenance tasks.
- Apply knowledge of large language models and AI systems to support the platform's AI-native architecture.
- Partner with systems-engineering, licensing, and quality-assurance organizations to help 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.
- For Track A, design and implement user interfaces using React, TypeScript, Tailwind CSS, and Vite.
- For Track A, develop full-stack solutions connecting front-end interfaces to AWS backend services, including Lambda, ECS, and DynamoDB, coordinating with senior engineers on more complex integrations.
- For Track A, create responsive dashboards and visualization tools for engineering workflows and AI agent interactions.
- For Track A, implement real-time communication through WebSockets and REST APIs.
- For Track A, support the design of maintainable, scalable front-end solutions for technical and engineering applications.
- For Track A, implement secure authentication and authorization systems for enterprise applications.
- For Track A, create and maintain CI/CD pipelines for web applications.
- For Track A, build proof-of-concept demonstrations to validate solution approaches with stakeholders before full development.
- For Track A, conduct user acceptance testing to ensure solutions meet real-world engineering requirements, and support user-developer feedback loops for rapid iteration.
- For Track B, design and implement autonomous agent architectures using AWS Bedrock and related services.
- For Track B, develop multi-turn agentic workflows with reasoning, planning, memory management, and tool calling for engineering and business contexts.
- For Track B, implement RAG and Graph-RAG systems using Amazon Neptune or equivalent knowledge-graph infrastructure for knowledge retrieval, requirements traceability, change-impact analysis, and design reuse.
- For Track B, build AI applications for automated requirements extraction and classification, traceability-gap detection, verification-artifact generation, design-review assistance, and cross-discipline consistency checking.
- For Track B, develop workflows using LangChain, LangGraph, and AWS Strands for moderately complex use cases, applying safety and alignment controls appropriate for regulated engineering.
- For Track B, support curation of golden datasets and benchmarks evaluating AI outputs against engineering ground truth, including requirements quality per the INCOSE Guide, traceability completeness, and configuration consistency.
- For Track B, support evaluation and safety pipelines using DeepEval, Ragas, or equivalent self-hostable frameworks that run within the GovCloud boundary and produce evidence suitable for NQA-1 and 10 CFR 50 Appendix B audits.
- For Track B, develop Model Context Protocol tools that expose engineering systems, reasoning capabilities, and agent workflows to the platform and external AI clients.
- For Track B, research and support implementation of emerging techniques in autonomous agent development.
- For Track C, support the design and build of the AWS-native data lakehouse/Common Data Environment using S3, Apache Iceberg or equivalent open table formats, AWS Glue Data Catalog, Lake Formation, and Athena as the governed substrate for AI agents and platform applications.
- For Track C, contribute to the canonical engineering data model spanning Xe-100 requirements, bills of materials, configuration items, test and simulation results, quality records, and digital-thread artifacts, aligned with ISO 19650 information-container principles.
- For Track C, support schema governance—including data contracts, schema registry, versioning, backward-compatibility rules, and deprecation workflows—across the platform's modular app ecosystem, and contribute to migration of platform services from per-app document stores to canonical lakehouse tables.
- For Track C, implement a tiered data-classification model covering public, internal, confidential, controlled, and restricted tiers, including 10 CFR 2.390 and ITAR/EAR-controlled tiers, enforced at the data layer through Lake Formation tag-based access control and row- and column-level security.
- For Track C, implement data lineage and provenance tracking using OpenLineage, AWS DataZone, or equivalent, supporting NQA-1 audit and 10 CFR 50 Appendix B traceability.
- For Track C, build Change Data Capture and event-driven pipelines that synchronize authoritative systems into the lakehouse using EventBridge, AWS DMS, Kinesis, and Glue streaming.
- For Track C, support integrations between customer, partner, and supplier engineering systems—including Siemens Teamcenter, PTC Windchill, Dassault 3DEXPERIENCE, Aras Innovator, Siemens Polarion, IBM DOORS/DOORS Next, Jama Connect, Oracle Primavera P6, Procore, SAP ERP, and Box—and X-energy's platform and lakehouse using AWS Glue, DMS, Kinesis, EventBridge, API Gateway, and Lambda.
- For Track C, parse, normalize, and map specialized engineering data formats including STEP (ISO 10303), JT, IFC, ReqIF, SysML v2 XMI, QIF, DWG/RVT, and proprietary PLM exports, aligned with ISO 19650 information-exchange requirements (OIR, PIR, EIR).
- For Track C, support identity federation design for external partners using SAML 2.0, OIDC, SCIM, AWS IAM Identity Center, Amazon Cognito, and cross-account IAM, and help enforce export control (ITAR, EAR, 10 CFR 810) and data residency at the integration boundary.
- For Track C, support definition of API contracts and versioning strategies; help monitor and troubleshoot cross-organizational data flows, including partner-side connectivity, schema drift, and SLA compliance.
- For Track C, support data-quality standards, validation pipelines, and metric dashboards that feed AI agent evaluation harnesses and NRC submission workflows.
- For Track D, design, build, and maintain containerized applications using Docker, including image building, testing, versioning, and production-deployment optimization.
- For Track D, develop and maintain GitLab CI/CD pipelines, including runner configuration, pipeline optimization, monitoring dashboards, and automated testing workflows.
- For Track D, support AWS infrastructure architecture using Terraform, including ECS, ECR, VPC, EC2, ALB/NLB, and other cloud services.
- For Track D, administer and help optimize AWS data services including DocumentDB, OpenSearch, Redis, Aurora Postgres, DynamoDB, and S3.
- For Track D, implement and maintain monitoring, alerting, and observability solutions using Datadog and CloudWatch.
- For Track D, support security and compliance requirements, including ACM certificate management and infrastructure security best practices.
- For Track D, contribute to release engineering efforts, including versioning strategies, deployment automation, and rollback procedures, and help apply cloud development lifecycle practices across platforms.
- For Track D, create testing frameworks for validating system behavior in serverless environments and configure and optimize container orchestration services for application deployment.
- For Track D, implement versioning and governance for code and dependencies using version control systems.
- For Track D, collaborate with development teams to optimize application performance, troubleshoot production issues, and implement infrastructure improvements.
- For Track D, participate in an on-call rotation to support system reliability and incident response.
- Contribute to technical specifications and roadmaps aligned with engineering needs, depending on scope.
- Serve as a technical point of contact between the development team and internal customers on assigned work, depending on scope.
- Help track product metrics and success criteria, depending on scope.
- Support evaluation and selection of appropriate AWS services, depending on scope.
- Produce system architecture diagrams and API documentation, depending on scope.
- Participate in technical reviews and code walkthroughs, depending on scope.
- Develop technical prototypes and proof-of-concepts, depending on scope.
Desired Qualifications
- Experience in the nuclear energy industry, aerospace, defense, or other highly regulated technical fields, including familiarity with NRC regulatory workflows.
- Prior experience contributing to AI products or internal platforms for engineering, manufacturing, or scientific use cases.
- Working literacy in digital engineering, including requirements (INCOSE Guide, ReqIF), MBSE (SysML v1/v2), ISO 19650 information management, digital thread, traceability, and verification and validation, and familiarity with Cameo Systems Modeler, Capella, or equivalent MBSE tools.
- Experience integrating PLM and requirements systems such as Teamcenter and Jama with platforms; familiarity with graph databases such as Amazon Neptune and Neo4j for traceability or cross-system entity resolution.
- Familiarity with NQA-1, 10 CFR 50 Appendix B, or equivalent software-quality frameworks; exposure to AI evaluation harnesses or data pipelines that produce evidence suitable for regulatory audit.
- Familiarity with AWS GovCloud and FedRAMP-authorized services; familiarity with ITAR, EAR, or 10 CFR 810 export control in technical work.
- Exposure to Model Context Protocol tool development.
- Familiarity with Idaho National Laboratory's Deep Lynx/Nexus or similar nuclear digital-engineering frameworks.
- INCOSE ASEP or CSEP certification; prior open-source contributions to AI, MBSE, or digital-engineering tooling.
About the company
X-energy designs and develops advanced nuclear reactors and fuel, aiming to commercialize small modular reactors based on a Generation IV high-temperature gas-cooled pebble-bed design and its TRISO-X fuel. The reactor uses ceramic-coated TRISO fuel in pebbles within a modular, sealed unit that operates at high temperatures to generate electricity or process heat, with safety features baked into the fuel and design. It differentiates itself by pursuing a specific Generation IV high-temperature gas-cooled, pebble-bed, TRISO-X fuel approach in a modular platform backed by significant financing to move toward commercialization. The company’s goal is to bring cleaner, safer nuclear energy to the market by completing design, obtaining regulatory clearance, and deploying its SMR technology and fuel at commercial scale.
Company Size
1,001-5,000
Company Stage
IPO
Headquarters
Rockville, Maryland
Founded
2009
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Simplify's Take
What believers are saying
- DOE raised Seadrift support to $2.15 billion on August 13, 2026.
- NRC issued Long Mott's FONSI in August 2026, clearing a major permitting hurdle.
- X-energy expanded Gaithersburg to 145,000 square feet, signaling hiring for commercialization and manufacturing.
What critics are saying
- Waterkeeper's NRC financial-qualifications challenge remains live; denial kills Long Mott's first commercial project.
- Dow's 4,500-job layoffs and $2.15 billion cost-share expose financing fragility through 2026.
- NRC safety review still runs through November 2026; any delay pushes commercial revenue beyond 2030.
What makes X-energy unique
- Xe-100 runs helium-cooled, 750°C reactors for industrial steam, not just electricity.
- TRISO-X fuel and graphite supply agreements lock safety-critical manufacturing around proprietary reactor design.
- Dow, Amazon, and Centrica pipeline spans 11-plus gigawatts across industrial and AI demand.
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Benefits
- 401(k) Retirement Plan
- Health Insurance
- Dental Insurance
- Vision Insurance
- Paid Time Off
- Tuition Reimbursement/Professional Development