• Lead a small team of strong individual contributors as a player-coach • Spend up to 50% of time contributing as an individual contributor • Provide hands-on technical guidance along with people, operational, and roadmap work • Collaborate closely with Product, Design, Customer Engineering, and adjacent engineering teams to turn customer pain into shipped product • Oversee the team's roadmap and weekly execution: scope and sequence work across multiple product surfaces

• Lead weekly planning, roadmap reviews, and cross-team syncs for Segmentation and Insights Platform, keeping delivery on track and stakeholders well-informed • Run 1:1s with engineers, with intentional focus on career growth, technical skill development, and early identification of blockers • Serve as the primary engineering DRI for cross-team dependencies — fielding requests from teams across Airbnb tech. and making clear, reasoned prioritization calls • Partner with the Product Manager to sequence the roadmap • Drive technical strategy for the Insights Intelligence Engine — Airbnb's emerging AI/ML anomaly and trend detection system — working across ML, Data Engineering, and Analytics Engineering disciplines • Oversee the design, delivery, and operational health of production agentic systems: autonomous pipelines, LLM-orchestrated workflows, and multi-agent architectures running at Airbnb scale • Champion AI-native development practices across both teams — from AI-assisted coding and review workflows to the use of agents in CI/CD, on-call response, and data quality monitoring • Own the health and operational maturity of both teams: on-call programs, incident retrospectives, SLO definitions, and runbook quality • Represent both platforms in org-wide planning cycles and contribute to the broader Marketing Technology engineering strategy.

Role Description We need a seasoned engineering leader who is equal parts technical builder, people mentor, and strategic operator. You’ll own engineering vision and execution for our renter and partner platforms, lead a team of ~60 engineers, and work closely with Product, Design, Data, ML, and Marketing leaders. This is not a steward role; our Engineering leaders are in the work, not above it. AI is collapsing competitive moats quarter by quarter, and we are rebuilding how we ship, what we ship, and the bar we hold ourselves to. As the engineering leader, you’ll elevate individual contributor growth, accelerate our adoption of AI across development workflows and product experiences, and build the systems and culture that allow engineering to be both fast and exceptional. What You’ll Do - Accelerate Building with AI - Drive adoption of AI-powered development tools (AI-assisted coding, automated testing, code review, agentic systems) to multiply engineering velocity. - Partner with Product and ML to embed AI into core product experiences — search, matching, personalization, and pricing. - Foster a culture of experimentation; ensure frontier capabilities show up in shipped products, not slide decks. - Define Technical Vision and Strategy - Lead a clear engineering vision aligned to our product, personalization, and marketplace strategy. - Ensure architecture enables rapid iteration, scalability, and reliability at scale. - Partner with the executive team to set strategic priorities through the lens of engineering capability. - Build and Lead a High-Performing Org - Set a clear performance bar. - Run rigorous calibration. Act decisively on underperformance. - Develop engineering managers and identify future leaders early; invest in succession planning. - Own recruiting strategy to attract and retain top engineering talent. - Create systems and rituals that drive velocity, collaboration, and accountability. - Elevate Quality, Velocity, and Individual Growth - Champion best practices: code quality, testing, CI/CD, observability, incident response, and architectural review. - Ship fast, fix fast, raise the bar every sprint. - Foundations earn their seat by enabling speed, not by slowing it down. - Evolve our platform and infrastructure for scalable, reliable, performant experiences. - Build clear career ladders and invest deeply in coaching, mentorship, and skill development across all levels. - Sweats the details: you believe the gap between a good product and a great one lives in the transitions, the edge cases, and the moments most people skip. You protect that gap. - Strengthen Cross-Functional Alignment - Serve as a strategic thought partner to Product, Design, Data, and ML leaders. - Bring technical feasibility and opportunity into every decision-making conversation. - Bring genuine appreciation for craft, interaction quality, and the details that create user delight. Partner with Design not just as a feasibility check, but as a co-owner of the experience. Qualifications - 8+ years leading engineering teams, including managing managers and scaling orgs of 40+ engineers in fast-paced, high-growth environments. - Strong technical foundation: modern web technologies, iOS & Android apps, distributed systems, cloud infrastructure, data-intensive applications. - AI-native track record: shipped AI-native products to production at consumer scale; drove measurable productivity gains from AI tooling — percent AI-assisted code, cycle time, defect rate — and can cite the numbers. - Performance management track record: you’ve raised the bar, made hard calls, and can talk about what changed afterward. - Marketplace or consumer product experience: built and scaled two-sided marketplaces or high-traffic consumer products where conversion, retention, and UX are critical. - People-first leadership: built cultures where ICs thrive, grow, and retain — and you know retention without a bar is just tenure. - Business-minded: connects engineering investment to business outcomes; makes smart tradeoffs between speed, quality, and scope. - Deep design partnership experience: you’ve worked closely with design leaders to ship products where the quality of micro-interactions, motion, and detail were treated as non-negotiable, not nice-to-have. Benefits - Lead engineering for a platform that helps millions of renters find homes. - Profitable, no fundraising pressure — operating with the urgency of a company that needs to win the next 24 months. - Competitive salary, bonus, and equity aligned to experience and market benchmarks. - A culture of velocity, calibration, and continuous learning. Company Description At Apartment List, we carefully consider a variety of factors to determine compensation for each position, including the role, level, and work. The US base salary range for this position is: - Zone 1: $300,000 - $350,000 TTC (including $255,000 - $297,000 base salary) + equity - Zone 2: $278,000 - $323,000 TTC (including $236,000 - $275,000 base salary) + equity - Zone 3: $255,000 - $297,000 TTC (including $217,000 - $252,000 base salary) + equity This reflects the compensation target for new hire salaries for the position across all US locations. Please note, the compensation details provided do not include benefits and perks that we offer. We also rely on market indicators along with considering your work location, job related skills, experience and relevant education and training, to determine compensation that is fair and competitive for you. Apartment List will consider paying compensation near the higher of the range in exceptional circumstances, where candidates have the experience, credentials or expertise that would warrant such consideration. It is always our goal to hire exceptional talent and we would be happy to share more about compensation during the hiring process.

• Lead, mentor, and grow a team of engineers who build the platform, pipelines, and interfaces that power catalog enrichment and ML access to catalog data. • Define and execute the technical roadmap, balancing new platform investments with reliability, observability, and developer experience for a growing user base. • Build and operate an AI-native enrichment platform that blends LLMs, classical ML, rules, workflow orchestration, and human review into pipelines non-engineers can configure and run. • Drive the evolution toward autonomous pipeline construction, where users express goals in plain language and the system assembles, evaluates, and optimizes workflows. • Own the ML-facing catalog data layer, including canonical product metadata and the policy controls that separate internal model inputs from customer-facing use cases. • Partner with ML, search, ads, commerce, and retailer teams to streamline data flows end to end and remove integration friction. • Advocate for clear, human-readable controls for source prioritization, rights management, licensing, and compliance to ensure auditable governance. • Boost developer and operator productivity via AI-assisted integration testing, investigation tooling, and on-call automation; set and meet SLAs on core attributes and model usage. • Contribute hands-on to architecture discussions, design reviews, and code reviews, especially in new or exploratory areas.