Engineering Manager, Core Product Engine
New
Fully remote-friendly work environment across CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8+ years of experience in backend engineering, distributed systems, or platform engineering, with 2+ years in an engineering leadership or management role.
- Required Skills
- AWSGraphQLLeadershipNode.jsTypeScriptDistributed Systems
Requirements
- 8+ years of experience in backend engineering, distributed systems, or platform engineering.
- 2+ years in an engineering leadership or management role.
- Strong hands-on experience with system design, particularly asynchronous, event-driven, or high-reliability architectures.
- Proficiency with modern backend technologies such as TypeScript, Node.js, GraphQL, and cloud platforms (AWS or equivalent).
- Demonstrated ability to lead complex refactoring or modernization of large-scale production systems.
- Strong analytical mindset with deep curiosity for debugging, edge cases, and system failure analysis.
- Proven experience balancing hands-on technical work with team leadership and cross-functional collaboration.
- Excellent communication skills with the ability to influence technical and non-technical stakeholders.
Responsibilities
- Lead the design, development, and evolution of backend orchestration systems that power critical end-to-end transaction flows across external insurance and partner systems.
- Drive the refactoring of legacy, tightly coupled automation systems into scalable, decoupled, and fault-tolerant architectures.
- Act as a hands-on technical leader, spending significant time coding, reviewing systems, and solving complex backend and distributed systems challenges.
- Define engineering standards for asynchronous workflows, state management, retry logic, and system reliability across distributed services.
- Partner closely with product, engineering, and executive leadership to translate business complexity into robust technical solutions.
- Guide the team in debugging edge cases, improving system observability, and increasing success rates across high-volume transactional flows.
- Contribute to the evolution of next-generation internal tools, leveraging AI-first approaches to scale the platform from millions to tens of millions of users.
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