VP of Engineering
C
CleverReal estate technology
Remote [United States]Full-TimeVp
Salary$250,000 – $300,000 / year
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Job Details
- Required Skills
- AWSPostgreSQLJavascriptRuby on RailsSoftware ArchitectureDebugging
Requirements
- Significant software engineering experience, including leadership of engineering managers and senior technical leaders.
- Strong technical depth across architecture, implementation, debugging, and production systems.
- Experience inheriting and evolving complex production systems, with judgment about when to extend, refactor, or replace them.
- Track record of improving engineering execution while building and developing high-performing teams.
- Strong product and business judgment, including close partnership with Product and executive leadership.
- Deep hands-on experience with frontier AI development tools and a strong point of view on their effect on software engineering.
- Experience helping a startup scale through multiple stages, including evolving its engineering team, operating model, and technical foundation.
- Experience leading a lean, high-autonomy engineering organization while remaining close to the technology.
- Experience modernizing or replacing significant legacy systems while supporting a live business.
- Experience with integration-heavy or operationally complex systems, such as marketplaces, CRMs, workflow automation, communications platforms, or third-party APIs.
- Experience using AI to materially change the speed or economics of major engineering work and enable non-engineering teams to build more safely.
- Familiarity with AWS, JavaScript, Python/Django, PostgreSQL, or Ruby on Rails, or experience in real estate, fintech, marketplaces, vertical SaaS, or another operationally complex business.
Responsibilities
- Lead Clever’s engineering organization and set expectations for technical quality, ownership, and execution.
- Set technical direction across core systems, deciding when to extend, simplify, re-architect, or replace existing technology.
- Review architecture and code, debug systems, address production issues, and contribute directly to critical work when appropriate.
- Improve the path from problem framing through implementation and production, simplifying scope and unblocking complex initiatives.
- Recruit, coach, and develop engineering talent through organizational design and performance management.
- Advance AI-assisted engineering and build platforms and guardrails that expand AI leverage across the company.
- Partner with Product and company leadership to shape solutions, challenge complexity, and make technical and organizational decisions.
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