Staff Software Engineer, Home & Cross-Retailer Search

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.

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.

Instacart’s Home & Cross-Retailer Search teams are responsible for how customers first discover where and what to shop: from the personalized Home experience to search across thousands of retailers and items. We own the systems that decide which retailers, items, and content to show, how fast they appear, and how well they match customer intent across platforms.

As a Staff Software Engineer on the Home & Cross-Retailer Search team, you will sit at the intersection of retrieval, distributed systems, and machine learning building the infrastructure that determines what tens of millions of Instacart customers see, find, and buy every day.

• Define and drive the multi-year technical vision for Home and Cross-Retailer Search infrastructure, spanning retrieval, ranking, indexing, and personalization at scale.
• Own the architecture of Instacart's cross-retailer search platform, ensuring correctness, freshness, and low latency as catalog and query volume grows.
• Own Home feed ranking and content strategy, retailer selection, and personalized recommendations driven by real-time and batch ML signals.
• Partner with ML Platform and Applied Science to productionize ranking models and improve experimentation infrastructure - A/B testing, interleaving, and offline eval
• Accelerate developer velocity across the sub-pillar: reduce time-to-production, build reusable components, and make it easy for product teams to experiment with minimal platform friction.
• Set the technical bar through design reviews, reliability standards, latency budgets, and observability practices.
• Lead major cross-org initiatives end-to-end, from scoping through rollout and post-launch ownership.
• Represent the engineering perspective in product and business planning, translating ambiguous problems into well-scoped technical strategies with clear tradeoffs
• Mentor and grow engineers across Home and XRS teams.

We're looking for someone energized by operating at this intersection - comfortable making hard tradeoffs, and able to influence technical strategy across organizational boundaries.

• 10+ years of software engineering experience, with a track record of leading large-scale distributed systems in production
• Demonstrated experience as a technical lead or architect on cross-team, multi-quarter initiatives  driving alignment, making hard tradeoffs, and delivering results
• Deep expertise in backend systems: high-throughput APIs, data pipelines, caching strategies, and storage systems.
• Experience building or scaling search, recommendations, or feed-ranking systems at significant traffic volume
• Strong command of system design principles: reliability, fault tolerance, observability, graceful degradation
• Proficiency in one or more of: Ruby, Go, Python, Java, or similar backend languages; comfort across the stack to debug and contribute where needed
• Strong communication skills - able to write crisp technical documents and drive alignment across engineering, product, and business stakeholders
• BS/MS in Computer Science, a related field.

• Experience at a marketplace or e-commerce platform with complex catalog, inventory, or fulfillment constraints
• Familiarity with ML serving infrastructure, feature stores, and online/offline evaluation frameworks
• Experience with real-time data pipelines (Kafka, Flink, Spark Streaming) and search indexing at scale (Elasticsearch, Solr, OpenSearch)
• Track record of improving developer productivity and platform health: reducing p99 latency, improving cost efficiency and cutting incident rates.
• Prior work on personalization systems using collaborative filtering, contextual bandits, or session-based signals

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