Senior Engineering Manager, Search

Instacart

4d•CA$229,000 - CA$241,500•Remote

About The Position

Instacart is the leading grocery technology company in North America, partnering with more than 1,800 retail banners to provide online shopping, delivery and pickup services from more than 100,000 stores. Search is the single most important way customers find and add products to their cart, and Cross-Retailer Search is how we help people decide not just what to buy, but where to shop. Together they sit at the top of the discovery funnel, where improvements in relevance and ranking compound directly into conversion, retailer engagement, and growth. We are standing up a dedicated Search engineering team and are looking for a seasoned engineering leader to run it. You will own the strategy and execution for Single-Retailer Search (SRS), Cross-Retailer Search (XRS), search suggestions and typeahead, and the whitelabel search we provide to Storefront Pro retailers. This is a heavily ML-weighted team operating one of Instacart's largest revenue surfaces, and one of the most exciting frontiers in applied search and ranking.

Requirements

4+ years of engineering management experience leading high-performing teams, with minimum 10+ years of total engineering experience.
Direct experience building or leading search, recommendations, ranking, or other applied ML systems, as a manager or as a senior individual contributor.
Familiarity with modern retrieval techniques, including neural/semantic retrieval, ANN, and LLM-based query understanding or re-ranking.
Strong technical depth across machine learning and large-scale distributed/backend systems; able to set direction with and earn the trust of staff-level engineers.
A track record of driving complex, cross-functional technical programs from strategy through launch while holding a high bar for quality and reliability.
Demonstrated product and business judgment: able to connect modeling and ranking decisions to metrics like conversion and revenue, and to reason through tradeoffs (e.g., relevance vs. latency, organic vs. ads).
Strong communication and stakeholder skills; comfortable bridging technical and non-technical partners.

Nice To Haves

Experience with ranking and personalization at scale: multi-stage rankers, multi-task deep models, embeddings, and real-time/session-based features.
Experience operating low-latency, high-throughput services with strict SLAs, including on-call and reliability ownership.
Experience leading a 0→1 or ambiguous product area, and driving alignment across teams where ownership boundaries are still forming.
Experience working with LLMs in production, and with experimentation/A-B testing infrastructure.
Exposure to two-sided marketplaces, e-commerce, or ads-adjacent ranking problems.

Responsibilities

Own the team's technical strategy, roadmap, and goals across Single and Cross retailer search, query understanding, suggestions, Ads on Search.
Drive top-line growth while holding a strict quality bar.
Champion the use of LLMs in search.
Partner with the platform team to design and ship the next-generation search retrieval architecture, while managing the latency and reliability tradeoffs of a tier-1 surface.
Double the team's experimentation velocity by investing in evaluation, AI-native debugging tooling, and ML foundations.
Partner closely with ML, Product, Data Science, the Home and Discovery Platform teams, the Ads organization, and whitelabel retailer teams to translate ranking changes into business and retailer outcomes.
Hire, develop, and coach engineers, and build an inclusive, high-trust team culture.
Roll up your sleeves on technical and architectural decisions as needed, while spending most of your time setting direction, removing blockers, and growing the people on your team.