Applications Integration Engineer

Kairos Power is an advanced nuclear energy company developing fluoride salt-cooled high-temperature reactors (KP-FHR) designed to deliver safe, affordable, and reliable clean energy at scale. The company takes an iterative development approach, building and testing reactor systems progressively to reduce technical and commercial risk before full deployment. Their technology combines proven reactor physics with innovative design to close the gap between advanced nuclear concepts and commercial viability. Kairos Power is currently constructing the Hermes demonstration reactor series in Oak Ridge, Tennessee, with permits from the U.S. Nuclear Regulatory Commission, marking a significant milestone in de-risking nuclear construction and supply chains for future commercial fleets. The company has formed the KP-OMADA advanced nuclear alliance, collaborating with major partners including Google and the Tennessee Valley Authority to pioneer new models for advanced nuclear deployment. Kairos Power pursues vertical integration by manufacturing reactor components, plant equipment modules, fuel, and molten salt coolant in-house across facilities in California, New Mexico, and Tennessee, enabling tight quality control and cost reduction. This comprehensive, self-reliant approach positions Kairos Power as a distinctive force in the clean energy transition, with nuclear energy central to its mission of decarbonizing the global energy system.

Job Summary

Kairos Power is seeking an Applications Integration Engineer embedded directly within the Operations Team in Oak Ridge, Tennessee. This role combines operational problem solving with deeper software and AI development capability. The engineer will work alongside Build Engineers, Operations Engineers, technicians, and leaders to create higher-complexity AI-enabled workflows and bespoke tools using secure capabilities provided by Kairos’s internal Development Team. The mission is not generic software development; it is to solve real problems in reactor build, integration, Test and Activation, fueling, and operations while respecting established engineering, Quality, Licensing, and operational approval authorities.

 

Responsibilities

• Troubleshoot integration failures, application defects, and data-flow issues across connected systems, and implement appropriate corrective actions.
• Validate application behavior and outputs against defined operational requirements, source data, and acceptance criteria before deployment or release.
• Monitor deployed applications and integrations for reliability, performance, and data-quality issues and support timely remediation.
• Identify high-value operational problems through direct engagement with field teams and translate them into practical AI-enabled solutions. 
• Build applications and workflows for work-instruction augmentation, lessons-learned capture, RFI support, configuration monitoring, engineering-change impact analysis, operational dashboards, and related use cases. 
• Develop RAG pipelines and application logic that combine controlled enterprise knowledge with operational workflows. 
• Integrate applications with approved APIs, MCP servers, model gateways, MES, PLM, ERP, issue-tracking systems, schedules, and other enterprise capabilities. 
• Develop structured outputs suitable for controlled downstream systems while preserving human review and approval. 
• Prototype rapidly with operational users, observe real use, and iterate based on field feedback. 
• Implement testing, evaluation, error handling, source traceability, observability, and appropriate human-in-the-loop controls. 
• Work with the Enterprise AI, Infosec, and IT teams on reusable integrations and deployment and maintenance of operational tools. 
• Help Build Engineers and Operations Engineers develop their own lightweight tools and raise the AI fluency of the broader Operations organization. 
• Maintain strong understanding of build execution and remain physically connected to the work. 
• Other duties as assigned.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, Engineering, or another technical discipline with strong demonstrated software capability, or an equivalent combination of relevant education and experience. 

• Typically 2+ years of software, data, automation, AI/ML, or technically sophisticated engineering experience; exceptional new graduates with substantial project portfolios may be considered. 

• Strong Python proficiency and working knowledge of APIs, JSON, SQL, Git, testing, and modern software development. 

• Hands-on experience building and deploying LLM applications, RAG systems, agents/tool-use workflows, or AI-enabled automation.
• Hands-on experience integrating applications with APIs, databases, or other software systems and troubleshooting application, data, or integration issues.
• Familiarity with one or more LLM orchestration or retrieval frameworks, vector databases, structured-output/schema tools, AI evaluation or tracing tools, and cloud or containerized deployment environments is preferred.
• Familiarity with MCP client/server concepts or comparable approaches for integrating AI applications with tools and enterprise systems is preferred.
• Familiarity with cloud services and containerized application deployment in AWS, Azure, GCP, or comparable environments is preferred.
• Familiarity with operational enterprise systems and engineering data such as MES, PLM, ERP, issue-tracking/work-management systems, Git repositories, CAD/BOM data, or comparable systems and data sources is preferred.

• Experience in industrial operations, manufacturing, aerospace, energy, construction, robotics, hardware integration, or other physical operations is strongly preferred. 

Knowledge, Skills & Abilities:

• Ability to trace and troubleshoot issues across application, API, data, and enterprise-system boundaries.
• Ability to validate, transform, and reconcile data exchanged among applications and enterprise systems.
• Ability to translate operational requirements into testable application behaviors and acceptance criteria.
• Ability to work with ambiguous operational requirements and turn them into usable prototypes quickly. 
• Ability to communicate with engineers and technicians and learn unfamiliar technical domains rapidly. 
• Ability to design and iterate solutions around operational user needs, adoption, and practical utility.

• Strong debugging, decomposition, and rapid-prototyping skills. 

• Ability to distinguish a platform problem from an application problem. 

• Comfort with incomplete data and imperfect enterprise interfaces. 

• Strong security and configuration-control judgment.
• Strong Python proficiency and working knowledge of APIs, JSON, SQL, Git, testing, and modern software development.

• Ability to teach and enable non-software engineers rather than becoming a bottleneck. 

• Excellent technical communication and documentation. 

Physical Demands

• Remaining in a stationary position, often standing, or sitting for prolonged periods 
• Moving about to accomplish tasks or moving from one worksite to another 
• Communicating with others to exchange information

Environmental Conditions

• General office environment
• High-concentration, demanding and fast-paced
• Prototyping/Testing environment
• Manufacturing/Industrial Environment 

Safety and PPE

• Reading and interpreting hazardous warning signs
• Reporting issues with equipment or unsafe conditions
• Wearing proper PPE, to include face mask, face shields, gloves, safety footwear, or other PPE as required

Travel

• Some travel between Kairos sites and partner facilities may be required. 

Certification

Additional Requirements

• Occasionally requires working weekends
• Occasionally requires schedule flexibility
• Occasionally requires extended hours to support launch and critical project timelines