Senior Staff Software Architect – Data Platform, AI/ML

🕒 il y a 21 jours

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GE Aerospace

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10 000+ employés

🏭 Fabrication

🎖️ Défense

💼 Conseil

Manufacturing • Defense • Consulting

GE Aerospace est un fournisseur de premier plan mondial de moteurs à réaction et turbopropulseurs, ainsi que de systèmes intégrés pour les avions commerciaux, militaires, d'affaires et d'aviation générale. L'entreprise s'engage à faire progresser l'aviation durable grâce au développement de moteurs d'avions efficaces compatibles avec les carburants alternatifs et collabore avec l'ensemble de l'industrie pour promouvoir l'innovation et la sécurité des vols.

Description

• 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

🎯 Exigences

• 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

🏖️ Avantages

• 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