Artificial Intelligence (ai) Platform Developer (mid-level or Senior)

Boeing Boeing · Aerospace · Seattle, WA +3

Boeing is seeking an AI Platform Developer to design, build, and deploy end-to-end AI applications, connecting AI/ML model inferences to user interfaces. This role focuses on the operational backbone of agentic AI solutions, including prompt engineering, vector database storage, and agentic workflows, ensuring reliability, observability, and security for production use. Responsibilities include bridging web architecture with MLOps, managing deployment and data pipelines, optimizing databases, and developing best practices for monitoring and troubleshooting.

What you'd actually do

  1. Build, test, and deploy end-to-end AI & Analytics applications, connecting AI/ML model inferences to functional user interfaces
  2. Bridge standard web architecture with machine learning operations (MLOps), handling model deployment and data pipelines
  3. Work with development teams and product managers to create software solutions
  4. Design client-side and server-side architecture
  5. Build the front-end of applications through visually appealing, responsive designs

Skills

Required

  • 3+ years of experience with software development, deployment, maintenance, and support
  • Experience troubleshooting technical system issues
  • Experience in production environments

Nice to have

  • 5 or more years' related work experience or an equivalent combination of education and experience
  • Experience supporting AI-enabled systems, automated workflows, and/or AIOps capabilities
  • Experience with observability tools, monitoring frameworks, logging, and/or alerting solutions
  • Experience with configuration management, provisioning, and/or release/deployment processes
  • Experience improving reliability, scalability, and/or operational readiness of software platforms
  • Experience working with service level indicators, SLAs, and/or error budgets
  • Experience integrating tools and systems in enterprise environments
  • Experience with cloud platforms, automation tooling, and/or modern deployment practices
  • Experience with strong analytical and problem-solving skills in fast-paced environments
  • Experience collaborating across delivery, platform, and operations teams

What the JD emphasized

  • AI Platform Developer
  • agentic AI solutions
  • operational readiness
  • reliability
  • observability
  • security
  • production use
  • MLOps
  • model deployment
  • data pipelines
  • prompt engineering
  • vector database storage
  • agentic workflows
  • troubleshoot
  • debug
  • upgrade software
  • technical system issues
  • production environments

Other signals

  • AI Platform Developer
  • agentic AI solutions
  • MLOps
  • operational readiness