We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca, AutoSync, Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence.
As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond.
This role will be within the AutoSync team. AutoSync supports over 3,500 dealerships nationwide, delivering cutting-edge software tools to simplify operations, boost marketing, and drive sales.
Role: Engineering Manager, Quality Engineering
Location: Toronto
ABOUT THE ROLE
At AutoSync, quality is owned by every product engineering team. The Quality Engineering team exists to make that possible at scale. We are looking for an Engineering Manager to lead a small, high-impact team focused on quality enablement, agentic engineering, tooling, metrics, and coaching. This is not a traditional QA management role, and it is not a centralized testing function. The team acts as a center of practice for quality: helping engineers and teams build, test, ship, and operate healthier products themselves.
A major part of this mission is helping AutoSync move from ad hoc AI prompting toward a mature "on-the-loop" agentic model. In this model, engineers supervise capable agents that can support planning, implementation, testing, triage, pipeline diagnosis, and quality improvement through clear workflows, guardrails, and measurable outcomes.
You will manage up to 5 direct reports and work closely with engineering managers, staff engineers, product leaders, platform teams, and cross-department stakeholders. This role is ideal for a technical people leader who can combine engineering judgment, quality strategy, agentic tooling, and organizational influence.
WHAT YOU WILL LEAD
Agentic Quality Engineering
- Define how AutoSync uses agentic coding tools such as Codex and similar platforms to improve engineering quality and developer effectiveness.
- Build, mature, and scale reusable testing and quality agents, skills, workflows, and integrations that serve multiple engineering teams.
- Establish practical patterns for agent supervision, validation, traceability, human review, and safe adoption.
- Help teams move from manual prompting to reliable on-the-loop workflows where agents reduce toil, and engineers stay accountable for outcomes.
- Evaluate emerging agentic tooling and translate useful capabilities into practical engineering workflows.
Quality Practice and Maturity
- Own and evolve AutoSync's quality maturity model, maturity indexes, standards, and KPIs.
- Coach engineering teams and individual engineers on modern testing, quality, and delivery practices.
- Embed quality practices into planning, delivery, release, and operational rituals.
- Participate in team ceremonies and cross-department planning where quality, delivery health, or engineering maturity are at stake.
- Shift the organization away from centralized test execution and toward product-team ownership of quality.
Metrics, Dashboards, and Quality Intelligence
- Design and build metrics and dashboards that show pipeline quality, product quality, release health, and engineering maturity.
- Provide visibility at team, product, and AutoSync-wide levels.
- Use data to identify quality risks, slow feedback loops, flaky tests, pipeline bottlenecks, escaped defects, and coaching opportunities.
- Help engineering leadership make better investment and tradeoff decisions using clear quality signals
Training and Enablement
- Create and run workshops, training sessions, and coaching programs for engineers and teams.
- Build practical playbooks, examples, golden paths, and knowledge bases for quality engineering and agentic workflows.
- Grow a community of practice around quality, testing, engineering health, and AI-assisted delivery.
People and Technical Leadership
- Manage, coach, and develop 3 direct reports.
- Set priorities and technical direction for the Quality Engineering team.
- Balance experimentation with operational reliability and measurable business impact.
- Model strong technical judgment, including the ability to reason about automation, pipelines, test strategy, and agentic workflows.
- Partner with engineering leaders across AutoSync to drive change without relying only on direct authority.
WHAT SUCCESS LOOKS LIKE
- Engineering teams have clear quality standards, measurable maturity indicators, and practical guidance they can use independently.
- Agentic workflows reduce manual toil in test generation, test maintenance, pipeline diagnosis, defect triage, and quality analysis.
- Quality dashboards are trusted by teams and leadership for planning, prioritization, and continuous improvement.
- Training and coaching lead to visible improvements in testing practices, release confidence, and product health.
- The Quality Engineering team is seen as an enablement partner and center of practice, not as a gatekeeper or outsourced test execution team
WHAT WE ARE LOOKING FOR
Required Experience
- Experience managing, coaching, and developing engineers in a software engineering organization.
- Strong background in quality engineering, test automation, CI/CD, or engineering productivity.
- Hands-on understanding of modern testing practices across unit, integration, contract, end-to-end, performance, and reliability testing.
- Practical experience with AI-assisted or agentic coding tools such as Codex, Claude Code, Cursor, GitHub Copilot, or similar tools.
- Ability to define quality strategies, maturity models, standards, KPIs, or engineering health metrics across multiple teams.
- Strong technical fluency in at least one modern programming language such as TypeScript, JavaScript, Python, Go, Java, or similar.
- Experience building or improving developer tooling, automation, dashboards, or quality platforms.
- Strong communication, coaching, facilitation, and stakeholder management skills.
- A platform and enablement mindset: success is measured by how much better other teams become, not by how much work is centralized in your team.
Preferred Experience
- Experience building or operating agentic workflows, including tool calling, agent orchestration, MCP servers, reusable skills, eval harnesses, or guardrails.
- Understanding of quality challenges in AI-assisted systems, including non-determinism, regression testing, output validation, hallucination risk, and human review.
- Experience with observability and quality dashboards using tools such as Grafana, Datadog, CloudWatch, Looker, or similar.
- Experience with cloud-native, distributed, event-driven, web, or mobile systems.
- Experience scaling quality practices across multiple product teams, domains, or business units.
- Experience in a center-of-excellence, center-of-practice, platform, or engineering enablement model.
- Experience designing and facilitating technical workshops, training programs, or internal communities of practice.
WHAT THIS ROLE IS NOT
- It is not a traditional QA manager role focused on assigning manual test execution.
- It is not a centralized team that writes and owns all test cases for product teams.
- It is not an AI experimentation role without delivery accountability.
- It is not only about dashboards or process. The role must connect metrics, tooling, agents, coaching, and engineering behavior change.
For a career where you can drive our business and shape your future, apply now.
