TELECOMMUTE Engineering Manager (Pre-LOS systems)
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Role details
Tech stack
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Job description
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Accountable for the safety, accuracy, and completeness of all code produced by your pod - whether generated by
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developers or AI, ensuring every AI-assisted code output passes through a named human reviewer.
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Enforce strict coding, architectural, security, and CI/CD standards across repositories, including project -specific
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guidelines (such as Cursor .cursorrules).
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Lead by example by writing clean, well-designed, and optimized code, particularly for complex core backend logic
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using C#, Wolverine, and Marten.
- Ensure systems operate with high reliability; direct production support, incident triage, and root -cause analysis.
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Run daily standups redesigned for the AI-First Development Lifecycle (AIDLC), focusing on resolving blockers and
- tracking AI tool performance.
- Direct the continuous flow of work using Kanban principles, aligning with Product Owners to ensure specifications
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are highly detailed.
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Partner with the Director, SVP, and Product Manager to ensure engineering execution aligns with organizational
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OKRs and product roadmaps.
- Direct career pathing, upskilling, and performance management for your engineers, championing training initiatives.
- Actively support and empower “AI Champions” within your pod to test, adopt, and deploy emerging tooling.
Requirements
- 8+ years of hands-on experience developing highly scalable web applications, distributed event-driven systems, and
- robust backend integrations.
- 3+ years of formal experience leading, mentoring, and scaling engineering teams.
- Expert-level mastery of modern C# development (including .NET Core, LINQ, and OOPS programming).
- Strong experience building asynchronous, message, and command-driven architectures using Wolverine and Marten
- (for document database storage and Event Sourcing).
- Extensive, practical experience working with relational and distributed NoSQL databases, specifically PostgreSQL
- (with Marten) and Azure Cosmos DB.
- Deep familiarity with modern AI coding workflows (e.g., Cursor, GitHub Copilot) and the ability to run code -review
- gates for AI-generated assets.
- Expert-level understanding of design-first principles (Spec Driven Development) and API contracting.
- Practical, deep knowledge of managing continuous flow, WIP limits, and pipeline metrics in a Kanban environment.
- Working knowledge of Azure Cloud Hosting and CI/CD pipeline management.
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