Company:

Who We Are

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.

About the Role

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.

Position Responsibilities:

Technical Execution in Support of Modernization

You'll be modernizing systems that have been running the business for years and building new ones that need to run it for years to come. Day to day that looks like:

• 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.
• Designing and implementing event-driven and microservices architectures that can scale, evolve, and be maintained by teams who didn't build them.
• 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.
• Mentoring and uplifting the developers around you — pairing, code review, and real-time feedback that makes the whole team better.
• Keeping product leadership and architects informed of technical risk, blockers, and changes that affect the engagement.

What We're Looking for You to Bring to the Table:

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've worked inside large enterprise environments with disparate/distributed systems and multi-cloud setups — you know how to navigate organizational complexity and deliver in spite of it.
• 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.
• Ability to translate ambiguous business problems into clear modeling approaches, assumptions, inputs, outputs, and success measures.
• 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.

Basic Qualifications (Required Skills/Experience):

• 5+ years of professional software development / engineering experience delivering production software in enterprise, cloud, or product development environments.
• 5+ years proven full-stack development experience building and shipping applications that include frontend user interfaces, backend services, APIs, and system integrations.
• 5+ years of hands-on experience writing clean, testable, production-quality code and participating in the full SDLC, including code review, debugging, testing, and deployment support.
• 3+ years of experience integrating AI, ML, or LLM capabilities into software applications, including working with model APIs, prompt orchestration, retrieval-augmented generation, or intelligent automation workflows.
• 3+ years of experience building or integrating AI/ML/LLM-powered product features in production, with awareness of lifecycle management, evaluation, monitoring, and operational risks.
• 5+ years of experience with modern software delivery practices, including source control, branching strategies, automated testing, CI/CD pipelines, and release management.
• 5+ years of experience working in complex enterprise or cloud environments, including distributed systems, multiple teams, shared platforms, or integration-heavy architectures.
• Demonstrated ability to collaborate effectively in a cross-functional team, partnering with Product, Design, Engineering, Data Science, Architecture, or Operations to deliver business outcomes.
• Must be legally able to work in Canada. 
• Individuals must not pose a risk for safeguarding of controlled goods. 
• Must be eligible to handle US export-controlled data.

Preferred Qualifications:

• Experience with cloud-native architecture and delivery tooling, such as containerization, Kubernetes or managed container services, infrastructure as code, and observability platforms.
• Experience modernizing legacy systems or working in brownfield environments, including approaches such as strangler fig, lift-and-refactor, or incremental modernization.
• Experience working in complex enterprise environments with distributed systems, legacy modernization, multi-team dependencies, and integrated data or application ecosystems.
• Experience designing or contributing to event-driven or microservices-based systems that are scalable, maintainable, and production-ready.
• Experience working with structured and unstructured data, including data cleaning, feature design, validation, quality checks, or analytical workflows.
• Experience in aerospace, industrial, manufacturing, transportation, or similarly complex regulated environments where reliability, integration, and operational support matter.
• Bachelor’s degree in Computer Science, Software Engineering, Electrical Engineering or Information Systems.

Conflict of Interest: 

Successful candidates for this job must satisfy the Company’s Conflict of Interest (COI) assessment process.  

Additional Information: 

This requisition is for a locally hired position in Canada. The employer is Boeing Canada.  Candidates must be legally authorized to work in Canada. Benefits and pay are determined by Canada and are not on Boeing US-based payroll. This is not an expatriate assignment. 

Please note that the information shown below is a general guideline only.  Pay is based upon candidate experience and qualifications, as well as market and business considerations. 

Salary pay range - $110,000.00 – $197,000.00 CAD 

Language Requirements:

Education:

Relocation:

Security Clearance:

Visa Sponsorship:

Contingent Upon Award Program

Shift: