Experienced or Senior Greenfield Software Developer

Boeing Boeing · Aerospace · Richmond, Canada, Canada

Experienced or Senior Software Developer at Boeing Vancouver focused on building full-stack, production-grade applications. This role involves modernizing existing systems and creating new ones, with a strong emphasis on integrating AI, ML, and LLM capabilities into client applications, including agentic workflows and RAG pipelines. The developer will also set up CI/CD pipelines, mentor other developers, and work within cloud-native architectures.

What you'd actually do

  1. Building full-stack, production-grade applications — frontend interfaces, backend services, REST and GraphQL APIs, and the integrations that tie them together in complex enterprise environments.
  2. Writing clean, testable, well-structured code across multiple languages and paradigms — and reviewing others' code with the same standard.
  3. Designing and implementing event-driven and microservices architectures that can scale, evolve, and be maintained by teams who didn't build them.
  4. Integrating AI, ML or LLM capabilities directly into client applications — building agentic workflows, RAG pipelines, AI-augmented developer tooling, and intelligent automation that actually works in production.
  5. Setting up and improving CI/CD pipelines, test automation, and delivery infrastructure so teams can ship with confidence.

Skills

Required

  • 3+ years of professional software development / engineering experience delivering production software in enterprise, cloud, or product development environments.
  • 3+ years proven full-stack development experience building and shipping applications that include frontend user interfaces, backend services, APIs, and system integrations.
  • 3+ years of experience with modern software delivery practices, including CI/CD, automated testing, and cloud-native architectures.
  • Experience leveraging algorithms and data-driven solutions for complex web or application features.
  • Ability to translate business needs into clear technical requirements, implementation approaches, and success criteria.
  • Experience working with application data, including validation, transformation, and integration across front-end and back-end systems.
  • Ability to evaluate solution performance using testing, metrics, and user or production feedback.
  • Familiarity with experimentation, monitoring, and data pipelines that support reliable application behavior in production.
  • Experience with cloud-native architecture — containerization, microservices, event-driven patterns.
  • Experience with source control branching strategies and CI/CD automation.
  • Experience building or being closely embedded with operations teams.
  • Understanding of cloud-native platform adoption, Kubernetes, managed container services, or other orchestration platforms.
  • Experience with infrastructure as code.
  • Experience with observability.
  • Experience building or integrating AI capabilities into real applications.
  • Experience using AI coding tools like Claude, Cursor, or Windsurf.

Nice to have

  • Experience with GraphQL APIs
  • Experience with functional and object-oriented programming styles
  • Experience with multi-cloud setups
  • Familiarity with strangler fig or lift-and-refactor approaches

What the JD emphasized

  • built production applications from scratch
  • modernized legacy systems
  • built or integrated AI capabilities into real applications
  • get an AI-powered or ML/LLM feature into production and keep it working

Other signals

  • integrating AI/ML/LLM capabilities directly into client applications
  • building agentic workflows
  • RAG pipelines
  • AI-augmented developer tooling
  • intelligent automation that actually works in production