Applications Integration Engineer

Kairospower; Oak Ridge (TN); On-site; USD 110,000 - 140,000; Full time

Job summary

Kairos Power seeks an Applications Integration Engineer in Oak Ridge, TN. This role blends operational problem solving with software and AI development to create AI-enabled workflows and bespoke tools with internal development support.

The engineer collaborates with Build and Operations teams to solve reactor build, integration, testing, activation, fueling, and operations problems while following engineering and regulatory controls.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, Data Science, Engineering, or similar with strong software ability.
• Typically 2+ years software, data, automation, AI/ML, or technically sophisticated engineering experience.
• 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.
• Familiarity with one or more LLM orchestration or retrieval frameworks, vector databases, and cloud/container deployment is preferred.
• Familiarity with MCP client/server concepts or comparable approaches for integrating AI applications with enterprise tools.

Responsibilities

• Troubleshoot integration failures, application defects, and data-flow issues across connected systems.
• Validate application behavior and outputs against requirements before deployment.
• Monitor deployed applications for reliability, performance, and data quality and remediate as needed.
• Identify high-value operational problems via field engagement and translate into AI-enabled solutions.
• Build workflows for work-instructions, lessons-learned capture, and operational dashboards.
• Develop RAG pipelines and application logic combining enterprise knowledge with workflows.
• Integrate applications with approved APIs, MCP servers, MES, ERP, and other enterprise systems.
• Develop structured outputs suitable for controlled downstream systems with human review.
• Prototype rapidly with operational users and iterate based on feedback.
• Implement testing, error handling, traceability, and human-in-the-loop controls.
• Collaborate with Enterprise AI, Infosec, and IT for reusable integrations and deployment.
• Assist Build/Operations Engineers in creating lightweight tools to raise AI fluency.
• Maintain strong understanding of build execution and stay connected to the work.

Skills

Python

LLM orchestration

RAG systems

AI-enabled automation

APIs/JSON/SQL

Git

Testing

Modern software dev

Cloud/container deployment

Education

Bachelor's degree in CS/Software Eng/Data Science/Engineering

Tools

APIs

JSON

SQL

Git

Job description

Company Overview

Kairos Power is a new nuclear energy technology and engineering company whose mission is to enable the world’s transition to clean energy, with the ultimate goal to dramatically improve people’s quality of life while protecting the environment. This goal will be accomplished through the commercialization of the fluoride-salt-cooled, high-temperature reactor (FHR) that can be deployed with robust safety, affordable costs, and flexible operation to accommodate the expansion of variable renewables.

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 reconc