Senior Staff Software Architect – Data Platform, AI/ML

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GE Aerospace

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10.000+ Mitarbeiter

🏭 Fertigung

🎖️ Verteidigung

💼 Beratung

Manufacturing • Defense • Consulting

GE Aerospace ist ein weltweit führender Anbieter von Jet- und Turboprop‑Triebwerken sowie integrierten Systemen für die zivile, militärische, Geschäfts- und Allgemeinluftfahrt. Das Unternehmen setzt sich dafür ein, die nachhaltige Luftfahrt voranzubringen – durch die Entwicklung effizienter Flugzeugtriebwerke, die mit alternativen Kraftstoffen kompatibel sind – und arbeitet branchenweit zusammen, um Innovation und Flugsicherheit zu fördern.

Beschreibung

• Define end-to-end data platform architecture from data ingestion through GenAI development by translating business requirements into technical solution designs and implementation roadmaps • Implement scalable architecture for AI solutions spanning machine learning, natural language processing, multimodal AI, and agentic systems • Architect multi-layer data transformation pipelines and design data models optimized for analytics and AI/ML workloads including dimensional schemas, feature stores, and aggregate tables • Build production-grade transformation code that converts raw operational data into trusted, analytics-ready datasets; implement incremental loading, schema evolution, and backward compatibility • Establish data quality and observability frameworks including automated validation, schema drift detection, lineage tracking, and data cataloging to support discoverability and trust • Ensure data architecture aligns with enterprise standards, cybersecurity requirements, data governance policies, and compliance obligations • Design and implement data security architecture; define access controls, data classifications, and retention policies that meet company compliance policies • Establish development workflows—branching strategies, pull request standards, code review processes, and deployment procedures • Build CI/CD pipelines for analytics applications and data transformations; implement automated testing, security scanning, and deployment automation • Build monitoring and alerting for both data pipelines and applications—tracking failures, performance, costs, and user issues • Define, build, and evolve AI-powered software products that accelerate operations including LLM applications, machine learning models, and intelligent automation for supply chain optimization • Develop Model Context Protocol (MCP) servers that package domain-specific AI capabilities for reuse across the enterprise • Package AI/ML models as robust, well-documented APIs that enable seamless integration into dashboards, applications, and operational workflows • Develop backend APIs and services that power analytics applications; implement authentication, authorization, caching, and performance optimization • Create reusable UI components and application templates that accelerate solution development; establish design patterns and code standards for application development • Mentor junior developers on software engineering best practices, application development patterns, and data modeling • Conduct code reviews for team contributions; provide feedback on code quality, performance, security, and maintainability • Provide technical guidance on solution optimization and application architecture • Create training materials and documentation that enable the team to build applications independently

🎯 Anforderungen

• Bachelor's Degree in Computer Science, Software Engineering, Data Science, or related field from an accredited university • A minimum of 3+ years of hands-on experience in software architecture, including building data platforms, pipelines, or applications in production environments • 2+ years building or integrating AI/ML models, applications, or intelligent features • Write production-quality code that meets standards and delivers intended functionality using the most appropriate technologies for the project (e.g., Python, Java, C#, TypeScript—based on system needs) • Experience building and implementing cloud data platforms; understanding of data architecture, ETL/ELT patterns, and data management best practices. • Proven experience with cloud data warehouses/lakehouses (Databricks, Snowflake, BigQuery, Redshift) • Expert-level SQL, query optimization, and performance tuning • Expertise in development platforms and services: AWS, Visual Studio, Databricks, GitHub, etc. • Experience implementing security frameworks, access controls, and deployment automation • Familiarity with ML workflows, feature engineering, and model deployment; able to integrate AI/ML into applications • Experience with prompt design, LLM orchestration, and agentic workflows / multi-agent systems

🏖️ Vorteile

• Healthcare benefits include medical, dental, vision, and prescription drug coverage • Access to a Health Coach from GE Aerospace • Employee Assistance Program, which provides 24/7 confidential assessment, counseling and referral services • Retirement benefits include GE Aerospace Retirement Savings Plan, a 401(k) savings plan with company matching contributions and company retirement contributions • Access to Fidelity resources and planning consultants • Tuition assistance • Adoption assistance • Paid parental leave • Disability insurance • Life insurance • Paid time-off for vacation or illness