About Urbanfix
Urbanfix builds AI/ML-powered software solutions for organizations that need to deploy AI capabilities without compromising on security, governance, or compliance. As our engineering organization scales, maintaining world-class software quality, engineering discipline, and delivery velocity becomes a strategic advantage.
We're looking for a Software Engineering Excellence Lead to build and continuously improve the engineering system that powers every product and every engineering team at Urbanfix.
The Mission
Your mission is to make Urbanfix's engineering organization one of the best in the industry. You'll define how software is engineered across the company by establishing standards, processes, tools, and practices that let teams build secure, scalable, maintainable, high-quality software — without slowing innovation.
You will not own product roadmaps or feature delivery. Instead, you own how software is built. Success is measured by improvements in engineering quality, productivity, predictability, and developer experience across the entire organization.
What You'll Own
- Software development lifecycle (SDLC)
- Engineering standards and best practices
- Architecture governance
- Code quality and maintainability
- Code review processes
- Development workflows
- Engineering productivity
- CI/CD engineering practices
- Testability and quality-by-design
- Technical documentation standards
- Reusable frameworks and libraries
- Technical debt management
- Engineering metrics and dashboards
- Developer onboarding and enablement
- AI-assisted software development standards
- Continuous improvement initiatives
Key Responsibilities
Engineering Standards & Software Craftsmanship Define and maintain company-wide standards: coding conventions, design patterns, clean architecture, SOLID principles, secure coding, performance, maintainability, scalability, documentation, and version control practices. Ensure consistency across every engineering team.
Engineering Operating Model Design and improve the engineering lifecycle: development workflows, branching strategies, PR standards, Definition of Ready/Done, technical design reviews, release processes, documentation requirements, and engineering governance. Lightweight processes that improve quality without bureaucracy.
Architecture Governance Partner with architects and tech leads to keep solutions modular, extensible, cloud-native, API-first, event-driven where appropriate, AI-ready, and maintainable. Facilitate architecture reviews and promote reusable design patterns without creating bottlenecks.
Engineering Productivity Reduce friction and increase efficiency: development tooling, IDE optimization, local dev environments, build performance, deployment automation, internal engineering platforms, developer self-service, AI-assisted development tools. Measure improvements with objective engineering metrics.
Code Quality Peer reviews, static code analysis, code quality gates, automated testing standards, complexity monitoring, refactoring strategies, technical debt reduction. Quality built in from the start, not inspected after the fact.
Software Delivery Excellence Work with DevOps and QA to improve CI/CD, deployment reliability, release quality, build stability, rollback strategies, feature flagging, and progressive delivery. Help teams ship faster while reducing production risk.
Engineering Metrics & Continuous Improvement Define, monitor, and improve deployment frequency, lead time for changes, change failure rate, MTTR, build success rates, PR cycle time, test coverage, escaped defects, technical debt, code review effectiveness, and developer productivity/satisfaction.
Engineering Enablement Build reusable assets: frameworks, starter projects, internal libraries, coding guidelines, documentation templates, architecture blueprints, technical playbooks, best practice guides.
Technical Leadership Coach engineering managers, tech leads, and senior engineers on software craftsmanship, engineering discipline, design/code reviews, mentoring, and engineering decision-making. Lead by influence rather than hierarchy.
AI-Driven Engineering Define standards for AI coding assistants, prompt engineering for developers, automated code generation, AI-assisted testing and documentation, and AI code review workflows — ensuring AI improves productivity without compromising quality or security.
Required Experience
- 8+ years of professional software engineering experience
- 3+ years in a senior technical leadership role
- Experience defining engineering standards across multiple teams
- Proven track record improving engineering quality and delivery performance
- Strong background in cloud-native software development
- Experience working with enterprise SaaS platforms
- Excellent understanding of modern software engineering practices
Technical Expertise
Software Engineering: Object-oriented design, domain-driven design, design patterns, Clean Architecture, SOLID principles, API design, event-driven architecture, distributed systems Development: JavaScript, REST APIs, Git Cloud & Platform: AWS, Docker, Kubernetes, Terraform (preferred), GitHub Actions or similar CI/CD Quality: Unit/integration/end-to-end testing, static analysis, SonarQube, test automation Engineering Practices: Agile delivery, DevOps collaboration, secure SDLC, observability, performance engineering
Leadership Competencies
Technical credibility, systems thinking, continuous improvement mindset, pragmatic decision-making, excellent communication, coaching and mentoring, cross-team collaboration, bias for automation, strong ownership and accountability.
Success in the First 12 Months
- Company-wide engineering operating model adopted by every development team
- Standardized coding practices, architecture reviews, and code review processes
- Meaningfully reduced lead time from development to production
- Increased deployment frequency while reducing production incidents
- Improved code quality and reduced technical debt through measurable initiatives
- Engineering dashboards with real-time quality and productivity metrics
- Better developer onboarding and reduced ramp-up time for new engineers
- AI-assisted development practices embedded without compromising quality
- A culture of continuous engineering improvement that scales with the company
📩 Interested? Reach out or apply directly.
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