Senior Technical Integrator

Boeing Boeing · Aerospace · Seattle, WA +2

This role focuses on integrating AI/ML capabilities into network infrastructure to enhance automation, predictive analytics, and anomaly detection. The Senior Technical Integrator will act as a liaison between IT business partners and stakeholders, collaborating with data scientists and network designers to operationalize models and ensure their performance in production. The role also involves developing documentation, managing vendor engagements, and staying current with AI/ML and networking trends.

What you'd actually do

  1. Lead integration and support of enterprise revenue generation transformation initiatives, with a primary focus on AI and ML-driven enhancements to network systems
  2. Act as the senior technical liaison to IT business partners and stakeholders, defining AI/ML strategies that align network capabilities with organizational and program goals
  3. Collaborate closely with data scientists, network designers, and security teams to operationalize models, ensure reproducibility, and maintain model performance in production environments
  4. Develop comprehensive documentation, runbooks, and training materials for IT partners to adopt and operate AI-enabled network capabilities
  5. Drive vendor and partner engagements for AI/ML products and managed services; lead proof-of-concept efforts and production readiness evaluations

Skills

Required

  • Project Management
  • technical integration
  • managing and/or leading network operations in a complex environment

Nice to have

  • Bachelor’s degree or higher
  • Project Management Certification
  • Experience driving a culture of can-do attitude and innovation

What the JD emphasized

  • AI and ML integration efforts across network infrastructure
  • operationalize models, ensure reproducibility, and maintain model performance in production environments

Other signals

  • AI/ML integration efforts across network infrastructure
  • enhance automation, predictive analytics, and anomaly detection
  • operationalize models, ensure reproducibility, and maintain model performance in production environments