Development Lead

Being part of Air Canada is to become part of an iconic Canadian symbol, recently ranked the best Airline in North America. Let your career take flight by joining our diverse and vibrant team at the leading edge of passenger aviation.

Join Air Canada—an iconic Canadian brand and North America’s top ranked airline—as we continue to evolve our digital platforms supporting critical operational and customer experiences.

The Development Lead is a senior, hands-on developer who drives sprint execution and delivery outcomes within an Agile delivery pod, and who practices AI-first, agentic engineering as the default way of working. This role owns delivery predictability, code quality, and release readiness while implementing solutions within the technical direction, architecture, and standards established by the Technical Lead and Development Manager.

As the most senior developer/lead within the pod, the Development Lead provides day-to-day technical leadership through delivery coordination, coaching, and hands-on contribution. They set up and run the pod’s AI agent workflows (coding, testing, review, and documentation agents working under human oversight), prove measurable productivity gains, and coach every developer in the pod to work the same way. The Development Lead is the primary execution authority within approved architectural and responsible-AI guardrails, escalating design decisions that fall outside defined patterns, and ensuring operational learnings are fed back into the backlog.

Let your career take flight by joining a team that’s redefining the digital passenger experience at the forefront of global aviation.

Responsibilities:

- Lead sprint commitments, delivery predictability, and delivery outcomes for the pod; proactively manage scope, dependencies, and trade-offs, and ensure stories are well defined, estimated, sequenced, and delivered as agreed.
- Shape the breakdown of complex requirements into clear technical tasks and agent-ready specifications (acceptance criteria, constraints, test cases) that both engineers and AI coding agents can execute against; anticipate risks early and guide the team through implementation and validation.
- Serve as the primary delivery execution authority within approved architectural guardrails; apply and enforce established patterns and standards, and escalate design decisions that exceed those guardrails to the Technical Lead.
- Lead by example in AI-first, agentic development: use AI coding agents (e.g., GitHub Copilot, Cursor, Claude Code) daily for design exploration, implementation, test generation, refactoring, and documentation, and coach the pod to adopt the same practices.
- Design, configure, and maintain the pod’s agentic development workflows, including multi-agent setups with clearly scoped roles (e.g., implementer, reviewer, test writer), version-controlled agent instructions and repository coding standards, scoped tool permissions, and reusable prompts and playbooks.
- Connect AI agents safely to the pod’s real systems of work (repositories, CI/CD, issue tracking, cloud, observability) through governed integrations such as
Model Context Protocol (MCP) servers, applying least-privilege access and secrets hygiene in partnership with Cybersecurity.
- Enforce human-in-the-loop guardrails: no destructive, production-impacting, or externally visible agent action without human approval, and no AI-generated change merged until it has been independently reviewed and verified by tests.
- Champion high-quality peer code and pull-request reviews, including AI-generated code, focusing on correctness, maintainability, performance, reliability, security, and adherence to approved patterns.
- Own the pod’s testing strategy, including test-driven development, unit, integration, and API test automation, and AI evaluation coverage, so that quality gates are consistently met and defects are prevented.
- Drive readiness for production releases, including completion of quality gates (tests, security checks, performance), runbooks/operational documentation, observability coverage, and rollback/mitigation plans.
- Uphold and enforce engineering standards for coding, testing, documentation, security, observability, and responsible AI practices within the pod.
- Enhance CI/CD pipeline efficiency, build automation, and AI-assisted development workflows (e.g., automated AI review and test generation in the pipeline) to improve deployment frequency and developer productivity.
- Lead and support complex or high-risk feature implementations, balancing delivery timelines with technical quality and operational risk.
- Partner with Product Owners, QA, Designers, and Scrum Masters to ensure clarity, feasibility, testability, and timely decision-making on scope changes.
- Provide first-level ownership for pod production issues and technical integrations; coordinate triage (using AI-assisted diagnosis where appropriate), restore service, and communicate status and mitigation to stakeholders.
- Lead root-cause analysis (RCA) for pod-owned incidents/defects and drive corrective and preventive actions; ensure learnings are translated into backlog items and completed.
- Establish and maintain clear, accurate, and up-to-date technical, prompt, and agent-instruction documentation to support maintainability, onboarding, and operational support.
- Monitor and improve delivery, quality, and AI-impact metrics such as defect rates, PR lead time, deployment frequency, rollback frequency, AI-assisted change share, and cycle-time improvement; use the data to report measurable gains and drive improvement actions.
- Evaluate and prototype emerging AI development tools and techniques; share what works with the Technical Lead and contribute pod learnings to IDD bootcamps, playbooks, and communities of practice.
- Provide day-to-day technical leadership and mentoring through pairing (including pairing on agent workflows), feedback, and guidance; foster a culture of craftsmanship, accountability, collaboration, and continuous improvement.
- Design, develop, integrate, maintain, and troubleshoot software applications and services; write, review, test, and debug code for new features and enhancements, and analyse requirements, dependencies, and system interactions to recommend implementation approaches.

Personal Attributes:

- Inspires and energizes engineering teams with a high level of enthusiasm, fostering a culture of excellence and ownership.
- Demonstrates a forward-thinking, innovative mindset—constantly exploring emerging technologies and unconventional solutions to complex challenges.
- Is a curious, hands-on builder who treats AI agents as everyday engineering tools, and is equally disciplined about verifying their output before it reaches
production.
- Builds and sustains a culture of trust, transparency, and psychological safety, enabling open dialogue and empowering diverse perspectives.
- Challenges assumptions and the status quo with curiosity and courage, driving continuous improvement and elevating team performance.
- Balances strategic vision with hands-on technical guidance, ensuring alignment between business goals and engineering execution.
- Leads by example with integrity, resilience, and a commitment to mentoring others toward their full potential.

Qualifications

Required

- Bachelor’s degree in Computer Science or a related field.
- Minimum five (5) years of experience in software development in a production environment.
- Demonstrated experience leading delivery execution within Agile teams, with accountability for sprint commitments, delivery outcomes, and code quality.
- Strong hands-on expertise with modern programming languages and frameworks (e.g., Java, Node.js, TypeScript, Python, React, React Native, Angular, NestJS), and solid grounding in APIs, event-driven, and cloud-native architecture.
- Demonstrated daily, hands-on use of AI-assisted and agentic development tools (e.g., GitHub Copilot, Cursor, Claude Code) in production work, with concrete examples of measurable impact on delivery speed or quality.
- Proven ability to write effective prompts and agent instructions, and to critically review and validate AI-generated code (spotting hallucinations, insecure patterns, and missing tests).
- Solid experience working with CI/CD pipelines, test-driven development, automated testing, and modern DevOps practices.
- Proven ability to uphold engineering standards, guide code quality, and support sprint-level delivery commitments.
- Strong communication skills with the ability to collaborate effectively across technical and non-technical roles.
- Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.

Assets

- Experience designing or orchestrating multi-agent development workflows (agent roles, scoped tool permissions, persistent memory/context, automated review gates).
- Experience connecting AI agents to engineering systems using Model Context Protocol (MCP) or similar tool integrations.
- Experience building AI features into products (LLM APIs, retrieval-augmented generation, tool calling) and applying AI evaluation frameworks and responsible AI practices.
- Experience with cloud platforms (AWS, Azure, GCP) and cloud-native architecture patterns; cloud certifications (e.g., AWS Solutions Architect or Developer) are an asset.
- Exposure to API platforms, integration technologies, or enterprise systems.
- Background in large-scale, regulated, or mission-critical environments such as aviation.
- A portfolio (e.g., GitHub, shipped side projects) showing software built end to end with agentic workflows.

Conditions of Employment:

Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment. Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest.

Linguistic Requirements

Based on equal qualifications, preference will be given to bilingual candidates.

Diversity and Inclusion

Air Canada is strongly committed to Diversity and Inclusion and aims to create a healthy, accessible and rewarding work environment which highlights employees’ unique contributions to our company’s success.

As an equal opportunity employer, we welcome applications from all to help us build a diverse workforce which reflects the diversity of our customers, and communities, in which we live and serve.

Air Canada thanks all candidates for their interest; however only those selected to continue in the process will be contacted.