Engineering Manager (Pre-LOS systems)

Essential Duties and Responsibilities:

• Accountable for the safety, accuracy, and completeness of all code produced by your pod — whether generated by

• developers or AI, ensuring every AI-assisted code output passes through a named human reviewer.

• Enforce strict coding, architectural, security, and CI/CD standards across repositories, including project -specific

• guidelines (such as Cursor .cursorrules).

• Lead by example by writing clean, well-designed, and optimized code, particularly for complex core backend logic

• using C#, Wolverine, and Marten.

• Ensure systems operate with high reliability; direct production support, incident triage, and root -cause analysis.
• 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
• are highly detailed.

• Partner with the Director, SVP, and Product Manager to ensure engineering execution aligns with organizational

• 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.

JD:

• 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.