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Principal - Software Engineer

Job in Rock Springs, Sweetwater County, Wyoming, 82901, USA
Listing for: GE Aerospace
Full Time position
Listed on 2026-10-03
Job specializations:
  • Software Development
    Full Stack Developer, AI Engineer (Applied/Software), Backend Developer, Software Engineer
Salary/Wage Range or Industry Benchmark: 152000 - 202000 USD Yearly USD 152000.00 202000.00 YEAR
Job Description & How to Apply Below
Job Description Summary

The Commercial Engine Services (CES) Business Intelligence (BI) team is building the next generation of analytics and AI-powered applications for supply chain and operations. We are looking for a Principal Software Engineer to design and build full-stack applications to turn operational data into AI-driven decision tools that predict, recommend, and act to drive business outcomes.

This is a hands-on, senior individual-contributor role: you'll shape our AI application strategy, build front-end and back-end services, embed AI features into production products, and create new products to solve our hardest problems. You'll partner with our BI developers and platform architect, and lead our junior software engineers to deliver high-quality solutions our business stakeholders can count on.

Job Description

Roles and Responsibilities:

Application Development & Delivery
  • Design, build, and maintain full-stack applications and services across the full software lifecycle: requirements, implementation, testing, documentation, and production support
  • Build responsive front ends and back-end services deployed to the cloud
  • Optimize application performance so applications and monitor applications for errors, latency, and usage; own alerting, incident response, and root-cause analysis
AI-Powered Features
  • Embed AI into applications with natural-language queries, predictive insights, recommendations, and conversational interfaces
  • Ground AI features in knowledge graphs and ontologies that model the domain and enable semantic search and reasoning over operational data
  • Build and expose reusable AI capabilities via MCP servers that applications and agents can call
  • Integrate machine-learning models and LLM APIs into production applications to enhance insights and decision-making
  • Build agentic workflows that trigger actions and update records, with human approval and audit logging
  • Partner with junior engineers to move models from experiment to reliable, production-grade features
Technical Standards & Code Quality
  • Set and enforce application coding standards, design patterns, and engineering best practices across the team
  • Serve as senior reviewer for application code correctness, performance, security, and maintainability
  • Establish CI/CD, automated testing, and version-control workflows for application development
  • Build reusable components, templates, and utilities that accelerate development across the team
Technical Leadership & Mentorship
  • Mentor and coach junior software engineers and BI developers
  • Translate ambiguous business problems into project plans and application work
  • Partner with BI leadership on the application roadmap and with stakeholders on requirements and priorities
  • Lead application projects of moderate to high complexity, guiding others and influencing technical direction
Required Qualifications:
  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field from an accredited university or college
  • Minimum of 8 years of hands-on experience building and shipping full-stack applications to production
Desired Characteristics:
  • Master's degree in a related field from an accredited university or college
Technical Expertise
  • Full-Stack Development:
    Strong across modern front-end and back-end technologies; builds and owns applications end to end
  • AI Integration:
    Experience embedding ML models, LLM APIs, and agentic workflows into production applications
  • MCP & Tool Interfaces:
    Builds MCP servers or equivalent tool interfaces that applications and agents call in production
  • Knowledge Graphs & Ontologies:
    Models domain knowledge as graphs and ontologies to ground AI, power semantic search, and enable reasoning over connected data
  • Cloud & Data Platforms:
    Familiar with cloud application…
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