Head of Engineering
Mainstay Labs Inc.
About Mainstay Mainstay is the leading market intelligence platform purpose built for buying, managing, and selling homes in the single family rental industry. As an AI native company, we turn complex data into clarity that helps the industry move forward with confidence. Founded within Opendoor, Mainstay launched as an independent company in 2024 and recently raised a Series A round led by Khosla Ventures. Ready to shape the future of real estate with AI? Join Mainstay and help us redefine what's possible in the single family rental space. If you thrive on solving complex problems and want to make a tangible impact in a fast-growing industry, we'd love to hear from you - apply now and let's move the industry forward, together! About the Role Mainstay's 25-person engineering team built the product. Now it needs a leader who can make that team perform like one twice its size, using AI tooling, sharper hiring, and better systems instead of adding heads. You will report to the CPO and partner closely with product, design, and operations. The goal is simple: give engineering a strong, credible voice in a product-driven company and ship faster with fewer people. In this role you will
- Lead the entire engineering organization (approximately 25 people) across all product engineering teams, including data engineering.
- Define what an AI-first engineering org actually looks like at Mainstay: tooling, workflows, performance standards, measurement, and team structure.
- Build an engineering culture where the bar is high, feedback is direct, and people get better fast. Culture here means operating standards, code review norms, and how the team makes decisions, not posters on the wall.
- Make clear, timely decisions about team composition and performance. Help strong engineers get significantly better through new tools and ways of working.
- Bring engineering a credible, trusted voice in product decisions. You know how to build influence through technical insight and delivery, and you help guide the roadmap through perspective and data
- Partner with the CPO and product managers on org design, hiring, and how engineering should evolve alongside the roadmap.
- Knows how to make a lean team punch above its weight. You're energized by increasing the velocity and output of the team you have, not by scaling headcount to solve problems. You've stayed close enough to the work to review a design doc, not just delegate it.
- Technical depth across distributed systems, data pipelines, and AI tooling, sufficient to guide architecture and earn the trust of senior engineers.
- You're a genuine thought partner on the roadmap - bringing technical depth, data, and strong opinions to the table - while trusting product to make the final call.
- Proven track record of increasing output and quality without defaulting to more headcount.
- Evidence of AI tooling you personally built or mandated into a production workflow your team owned.
- Experience leading engineering at a Series A or Series B startup and operating a lean, high-output team.
- Background in a company or team known for high-performance engineering standards and execution speed.
- A clear point of view on how to redesign the way a team builds in an AI-native environment - not just which tools to adopt, but how the workflow itself should change.
- Experience at a company where data correctness and operational reliability are core product features, not afterthoughts.
- You care more about what your team shipped last quarter than what your title says.
- You believe in smaller, sharper, AI-amplified teams and have started building them.
- You have built in environments where the process did not exist yet and you had to create it while shipping. That is the job here.
- You navigate the product-engineering interface without treating it as a political problem.
- You will spend your first month in the code, in 1:1s, and in the data before making structural changes.
- You want to build a 100-person org or lead by adding layers, managers, and heavy process.
- You're most comfortable when engineering sets its own direction rather than building in close partnership with product.
- You talk about AI transformation more than you build durable, real-world AI workflows.
- You need a polished environment before you can move, or tend to operate in a highly political way.
Vacancy posted 2 days ago
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