Sr Software Engineer
Job
GE Aerospace
Remote
$111,000 Salary, Full-Time
Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
88
out of 100
Average of individual scores
Skill Insights
Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.
Job Description
- Job Description Summary
- The AI Systems Team is building the next generation of AI-assisted tooling for aerospace engine design.
Own the full software lifecycle:
requirements analysis, solution design, implementation, documentation/procedures, testing, deployment, and operational support. Convert complex engineering datasets into reliable, scalable workflows that enable modeling, inference, and decision support in design and manufacturing contexts.- Job Description
Roles and Responsibilities:
- + Define, develop, and evolve
- AI-enabled software products and platforms
- that accelerate aerospace
- design engineering workflows
- , leveraging large-scale
- simulation, test, and manufacturing data
- + Provide hands-on technical leadership for an Agile team of 8-10
- engineers
- , setting architecture, coding standards, and delivery practices while remaining close to implementation + Partner with Control Title Holders and engineering stakeholders to understand product vision and translate design-engineering needs (e.g., performance, durability, operability) into software and AI capabilities + Translate requirements into a
- prioritized backlog
- of epics/user stories, driving delivery to required
- timelines, quality, security, and operational
- standards. + Collaborate with architects and domain experts to develop and execute
- multi-generation technology roadmaps
- for AI, data, and platform modernization (e.g., simulation-data pipelines, model serving, evaluation, and governance) + Lead the design and implementation of
- data/ML pipelines
- that ingest and curate simulation outputs (CFD/FEA/thermal/structural), test data, and engineering metadata—enabling analytics, surrogate modeling, optimization, and AI-assisted decision support + Build and operate
- cloud-native services
- on •AWS and Azure•, including secure storage, scalable compute, orchestration, and MLOps capabilities (e.
- shared data products, common APIs, feature/model registries, templates, and reference architectures
- + Establish and improve engineering processes across development, sustainment, and production support—improving reliability through
- observability, incident response playbooks, automated remediation, and post-incident learnings
- + Work cross-functionally with other business departments (engineering, manufacturing, quality, IT/security) to align dependencies, compliance requirements, and deliverables + Drive world-class quality through rigorous SDLC practices:
- Lean/Agile/XP
- , CI/CD, automated testing, secure coding, scalability patterns, documentation-as-code, refactoring, and performance engineering + Ensure the team has clear understanding of business direction, strategy, priorities, and measurable outcomes; communicate consistently and transparently + Engage subject matter experts to ensure successful transfer of complex domain knowledge (e.
- data structures and algorithms
- , implementing efficient approaches for large datasets, scientific computing workflows, and high-throughput services + Proactively share information across the team and stakeholders with the right level of detail, strong timeliness, and clear technical rationale
Required Qualifications:
- + Bachelor's Degree from an accredited college or university (or a high school diploma / GED with a minimum of 4 years of relevant working experience + At least an additional 3 years of relevant working experience
Desired Characteristics:
- + Proven experience building
- data platforms and ML systems
- for engineering/scientific data (simulation, test, telemetry, manufacturing, or similar). + Strong cloud expertise across
- AWS and Azure
- , including architecture, security, and operations + Experience with
- MLOps
- practices: experiment tracking, reproducible training, model registry, CI/CD for ML, automated evaluation, monitoring/drift detection, and controlled rollouts. + Experience building
- APIs and services
- for AI-powered applications (REST/gRPC), plus strong data access patterns and query optimization.
- Business Acumen
- + Demonstrates initiative to explore alternate technologies and approaches, using clear tradeoff analysis (cost, risk, performance, security, maintainability).
- Leadership
- + Leads by example: delivers while mentoring, coaching, and unblocking team members. + Drives alignment across product and engineering, communicates decisions clearly, and influences outcomes with data and structured reasoning. + Continuously measures deliverables against commitments; balances competing objectives while maintaining delivery predictability and quality.
- Personal Attributes
- + Strong written and verbal communication skills; able to translate between domain experts and software/ML teams.
- Additional Information
- GE Aerospace offers a great work environment, professional development, challenging careers, and competitive compensation.
Relocation Assistance Provided:
- No \#LI-Remote - This is a remote positionGE Aerospace is an Equal Opportunity Employer.
Similar remote jobs
Similar jobs in Houston, TX
MD Anderson Cancer Center
Houston, TX
Posted2 days ago
Updated9 hours ago
Baylor College of Medicine
Houston, TX
Posted2 days ago
Updated9 hours ago
UTHealth Houston
Houston, TX
Posted2 days ago
Updated9 hours ago
Similar jobs in Texas
Connally Independent School District
Waco, TX
Posted2 days ago
Updated9 hours ago
Texas Department of Public Safety
Austin, TX
Posted2 days ago
Updated9 hours ago