Senior Greenfield Full Stack Developer

Senior Greenfield Full Stack Developer (Builder) Company: Boeing Vancouver At Boeing Digital Services, we focus on practical innovation that drives tangible results for the aerospace industry. Our team leverages advanced technology and data analytics to develop solutions that enhance operational efficiency and meet the needs of our customers. We are dedicated to creating intuitive, scalable, and secure solutions that empower our customers, partners, and empowered team to succeed. Join us in creating the future of aviation technology, where your contributions will shape impactful solutions for airlines around the globe. We're looking for an Senior Greenfield Full Stack Developer (Builder) who will help support the end-to-end software delivery. This is first and foremost grounded in Software Developers who bring both passion and experience in leveraging the latest AI tools to build cloud-native systems for cutting edge digital aircraft maintenance products. You will work closely with other Developers (Builders), Product, Design, Tech Leads, Architects, and Data Science to deliver product features and capabilities that keep AI/ML at the center. This role is a hybrid position (2 days per week) and can be worked out of our Richmond, BC office. Technical Execution in Support of Modernization 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. Writing clean, testable, well-structured code across multiple languages and paradigms — and reviewing others' code with the same standard. Write tests (unit, integration, system etc) and integrate them across the development process. Ensuring quality from local development to deployment. 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. Setting up and improving CI/CD pipelines, test automation, and delivery infrastructure so teams can ship with confidence. Keeping product leadership and architects informed of technical risk, blockers, and changes that affect the engagement. Software Development Execution to Support Modernization You've built production applications from scratch and modernized legacy systems — comfortable with both greenfield and brownfield and know when approaches like strangler fig or lift-and-refactor are appropriate. You're fluent in multiple programming languages and paradigms — clean, testable code in both functional and object-oriented styles, knowing how to pick the right tool for the job, including when to reach for AI-assisted development. You've delivered full-stack solutions — frontend web apps, backend APIs, cloud-hosted services, and standalone applications — and understand how those pieces fit together end-to-end in complex enterprise environments. You're comfortable owning your part of the software development lifecycle (SDLC) end-to-end — writing code, reviewing pull requests (PR’s), writing tests, and empathizing with developers on either side of you. You understand cloud-native architecture — containerization, microservices, event-driven patterns — and are comfortable with source control branching strategies and CI/CD automation. You've either built or been closely embedded with operations teams — you understand cloud-native platform adoption, whether that's Kubernetes, managed container services, or other orchestration platforms depending on client environment, infrastructure as code, observability, and what it means to build software that can be run in production. Data, Modeling, and Applied Algorithms Experience designing and implementing algorithms for complex product or operational problems. Working knowledge of statistical modeling, machine learning, optimization, forecasting, simulation, or other quantitative methods. Experience working with structured and unstructured data, including data cleaning, feature design, validation, and quality checks. Ability to evaluate model or algorithm performance using appropriate metrics, test data, error analysis, and production feedback. Experience turning data analysis into product or engineering decisions. Familiarity with data pipelines, analytical workflows, experimentation, and monitoring for model or algorithm behavior in production. AI and Intelligent Systems You've built or integrated AI capabilities into real applications — you know what it takes to get an AI-powered or ML/LLM feature into production and keep it working. You use AI coding tools like Claude, Cursor, or Windsurf as a natural part of how you work — as a way to move faster and produce higher quality output every day. 5+ years of professional software development / engineering experience delivering production software in enterprise, cloud, or product development environments. ~5+ years proven full-stack