Senior Engineering Manager, Search

Remote from: Canada
Salary, yearly, USD: 229,000 - 241,500
Department: Software Engineering
Employment type: Full Time,
Job posted: 5 Jun 2026
Apply before: 5 Jul 2026
Experience level: Senior
Views / Applies: 20 / 0

Instacart invites the world to share love through food. This is how homemade is made.

Internet
2012

AI Summary

This is a Senior Engineering Manager role at Instacart, leading the Search engineering team. The role involves owning the technical strategy for single and cross-retailer search, including search suggestions and whitelabel search. The team is heavily ML-weighted and operates one of Instacart's largest revenue surfaces. The manager will drive growth, champion LLMs in search, and partner with multiple teams. The role requires 4+ years of engineering management experience and direct experience with search, recommendations, or applied ML systems.

Role DNA

Job Complexity

Easy Hard

Pace & Pressure

Relaxed Fast-paced

Autonomy Level

Guided Full Ownership

Communication Load

Independent Highly Collaborative

AI Insight Leading a large-scale search system with ML and infrastructure requires deep technical expertise and cross-team coordination, placing high demands on leadership and problem-solving.

Salary Analysis

AI Insight The offered salary range of $229,000-$241,500 is competitive for a Senior Engineering Manager role in the US market, especially considering the company's equity and benefits. It aligns well with industry standards for top-tier tech companies.

Key Skills

Engineering Management Search Systems Machine Learning Large-Scale Systems LLMs Ranking & Relevance Cross-Functional Leadership Technical Strategy Team Building Experimentation

Cover Letter Sample

Dear Hiring Manager,

I am writing to express my strong interest in the Senior Engineering Manager, Search position at Instacart. With over 10 years of engineering experience and 4+ years managing high-performing teams, I have a proven track record of leading search and ML systems that drive growth and user engagement. My expertise in modern retrieval techniques like LLMs and neural search aligns perfectly with the team's focus on ranking and relevance.

I am particularly drawn to Instacart's mission of transforming the grocery industry and the opportunity to own the strategy for a critical revenue surface. I look forward to leveraging my experience to double experimentation velocity and build an inclusive team culture. I am confident I can contribute to Instacart's continued innovation in applied search.

Sincerely, [Your Name]

Possible Interview Questions

How would you approach improving search relevance for a cross-retailer platform like Instacart?

I would start by analyzing user behavior data and identifying key metrics like click-through rate and conversion. Then I'd prioritize improvements like query understanding using LLMs, incorporating contextual signals (e.g., time of day, location), and personalizing results based on user preferences. I'd also invest in A/B testing infrastructure to validate changes.

Describe your experience leading ML-heavy engineering teams. How do you balance technical debt with feature development?

I've led teams building ranking and recommendation systems. I advocate for allocating a fixed percentage of time (e.g., 20%) to tech debt reduction and infrastructure improvements. I also ensure team members understand the long-term value of robust foundations, and I celebrate wins from both new features and system enhancements.

How would you incorporate LLMs into Instacart's search system?

LLMs can enhance query understanding by parsing complex natural language queries (e.g., 'gluten-free pasta under $5') and generating semantic embeddings for retrieval. They can also be used for re-ranking to capture nuanced relevance. I would start with a pilot on a specific use case, measure impact, and iteratively expand.

What strategies would you use to double the team's experimentation velocity?

I'd invest in building a self-serve experimentation platform with automated metric tracking and statistical analysis. Reducing the time to set up experiments by standardizing templates and data pipelines would also help. Additionally, fostering a culture of rapid iteration and clear success criteria would encourage faster decision-making.

How do you ensure alignment between Engineering, ML, Product, and Data Science teams?

I establish shared OKRs and hold regular cross-functional syncs to review progress and dependencies. I also encourage embedded team members (e.g., MLEs, data scientists) to participate in planning and retrospectives. Clear documentation and transparent communication about trade-offs help maintain alignment.

We’re transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work.

Overview

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.

About the job

You will lead and grow a senior team of engineers, partnering with embedded MLEs and ML leads, responsible for the relevance, ranking, and infrastructure behind Instacart Search. In this role, you will:

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.

You’ll 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.

Minimum qualifications

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.

Preferred qualifications

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.

#LI-Remote

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here. Currently, we are only hiring in the following provinces: Ontario, Alberta, British Columbia, and Nova Scotia.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.

For Canadian based candidates, the base pay ranges for a successful candidate are listed below.

CAN

$229,000—$241,500 USD

Apply now >