Instacart

Compensation

Full Description

Overview Instacart's AI Labs and Experiences team is building the next generation of product experiences that make grocery shopping smarter, more engaging, and more personal. Our AI Experiences team is focused on delivering customer- and shopper-facing features powered by large language models and modern machine learning across web and mobile-think conversational shopping, smart lists, meal planning, and personalized discovery at scale. As a Senior Engineering Manager, you will lead and grow a high-performing engineering team to invent, ship, and iterate AI-first experiences that reach millions of people, weekly. You'll partner closely with AI Labs leadership, working directly with founders and senior engineering leadership, while driving a roadmap that meaningfully moves core business metrics. This is a fast-paced, highly collaborative environment where we roll up our sleeves, move quickly, and put it all on the table. If you're energized by building zero-to-one products, scaling teams, and delivering measurable impact, we'd love to hear from you. This role is open to candidates based in the United States or Canada. About the Job • Lead, coach, and develop a team of 10+ engineers building AI-powered shopping and merchant experiences across mobile and web, fostering an inclusive, high-trust culture. • Own end-to-end delivery of AI features (e.g., conversational search, smart lists, meal planning, personalization), from roadmap and scoping to launch and iteration, anchored to clear OKRs. • Provide technical leadership across LLM systems, including prompt orchestration, retrieval-augmented generation (RAG), safety/guardrails, online evaluation, and latency/cost optimization. • Partner cross-functionally with Product, Design, Data Science, Research, and Operations; influence strategy and prioritization through clear communication and data-driven decision making. • Establish engineering excellence: code quality, testing, observability, SLOs, incident response, on-call health, and privacy/security best practices for PII and model safety. • Hire exceptional talent, manage performance, and create career growth paths; help shape the team's operating model and rituals as we scale. • Measure business impact via instrumentation and A/B testing; rapidly iterate based on insights to improve conversion, retention, and user satisfaction. About YouMinimum Qualifications • 10+ years of professional software engineering experience, including 4+ years directly managing software engineers (hiring, performance management, and career development). • Track record leading teams of 8+ engineers to deliver high-impact consumer or marketplace features in production. • Hands-on experience building and shipping ML/AI-powered product experiences, including integrating modern LLMs or large-scale NLP systems in production (e.g., RAG, prompt engineering, safety/guardrails). • Proficiency in at least one backend language (e.g., Python, Go, Java) and with a major cloud platform (AWS or GCP); strong SQL skills for data analysis and instrumentation. • Experience designing, operating, and scaling services with clear SLOs, on-call ownership, observability, and incident response. • Practical experience with experimentation platforms and A/B testing, defining success metrics, and making data-informed decisions. • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. • Located in and eligible to work in the United States or Canada. Preferred Qualifications • Experience leading multiple teams or managing managers, including scaling an organization from early stages to 10+ engineers. • Deep experience with LLM ecosystems: vector databases/embeddings, evaluation frameworks, hallucination mitigation, fine-tuning, or RLHF. • Background in e-commerce, search/recommendations, ads, or large-scale consumer applications with millions of users. • Experience optimizing LLM inference for cost, latency, and reliability; familiarity with model/provider evaluation and vendor management. • Familiarity with security, privacy, and compliance considerations for AI systems (e.g., SOC 2, GDPR/CCPA) and safe AI practices. • Advanced degree in Computer Science, Machine Learning, or related field.