House Engineering Manager - Cloud Diagrams

About the Role

Lead a high-performing engineering team to deliver innovative cloud diagramming solutions, driving technical excellence and team growth in a hands-on leadership role.

Responsibilities

• Lead and mentor a team of 5-10 engineers, fostering a high-performance culture.
• Drive daily operations, unblock team members, and ensure clear delivery of value.
• Oversee the engineering release process, monitor deployments, and uphold production standards.
• Review pull requests, provide constructive feedback, and lead technical design discussions.
• Own the team's technical roadmap, assess technical debt, and ensure system scalability.
• Collaborate with Technical Product Owners and UI/UX Designers on sprint planning and roadmap alignment.
• Manage incoming business needs, customer support tickets, and balance sprint commitments with customer-facing responsibilities.
• Drive an AI-Driven software development lifecycle, ensuring quality while leveraging AI for implementation.
• Communicate effectively upwards, downwards, and sideways to ensure alignment and collaboration.

Requirements

• Proven experience leading an engineering team (5+ engineers) in a delivery-focused environment (3+ Years).
• 5+ years of past experience as a software engineer.
• Strong hands-on technical background with the ability to review code, guide design, and dive deep.
• Experience owning delivery and execution, including sprint planning and backlog management.
• AI-Driven mindset, prioritizing AI while ensuring quality and consistency.
• Demonstrated ability to mentor, coach, and grow engineers.
• Strong communication skills, translating business context into technical direction.
• Experience in SaaS, cloud-native, or distributed systems environments.
• Strong hands-on experience with Node.js (backend services, APIs, real-time systems).
• Strong hands-on experience with React (complex state management, performance optimization).
• Deep understanding of modern web architecture and browser performance.
• Solid experience designing and operating systems in cloud environments (AWS, GCP, Azure).
• Practical experience with Kubernetes (K8s), including cluster architecture and troubleshooting.
• Strong understanding of cloud networking fundamentals (VPCs, routing, load balancers, security, DNS).
• Clear understanding of network plumbing across clouds and VPCs.

Nice-to-Haves

• Experience with GenAI and its application in development workflows.
• Specializations in Kubernetes, GenAI, or CloudOps.
• Experience working with award-winning cloud partners (AWS, Google Cloud, Microsoft Azure).