Jobs at Babylist

Lead and own a broad domain end-to-end: set multi-team architecture and roadmap, build platform and tooling, ship production systems, define AI standards and evals, partner with product/design/data, coach senior engineers, and solve high-impact technical and product problems.

Own end-to-end engineering problems across Babylist's Rails monolith and AI-enabled systems. Design, ship, and iterate on features and abstractions, run experiments, harden critical paths, review risky changes, and share AI learnings. Work across backend, frontend, mobile, data and ML infrastructure to improve customer outcomes and platform reliability.

Own the technical product lifecycle for Merchandising and Owned Brands: evaluate/build a PIM, replace manual Google Sheets workflows, design systems integrations and APIs, embed with stakeholders to find greenfield automation opportunities, define metrics, partner with engineering and data, and apply AI to accelerate discovery and delivery.

Lead end-to-end ownership of a major consumer product surface, set one-year strategy and quality standards, use AI-native tools to prototype and ship, mentor PMs, define KPIs, and drive measurable business impact while raising the team's AI-product craft.

Own end-to-end product experiences across web and native mobile: set design vision, run user research, rapidly prototype (AI-enabled), write production frontend code, evolve design systems, mentor designers, and drive measurable product outcomes.

Own and evolve Babylist's AWS infrastructure, Terraform IaC, Kubernetes/EKS clusters, CI/CD, and observability for a platform serving millions. Lead incident response, improve developer tooling, and set reliability standards across engineering teams.

Lead product for personalization and discovery across Babylist: own strategy, KPIs, and quality for recommendations and feed surfaces. Partner with ML engineering on retrieval, ranking, candidate generation, and evaluation. Drive one-year roadmap, commercial impact, AI-native prototyping, and mentor PMs while raising company-wide judgment on ML investment and implementation.

Lead end-to-end product design across web and native, run user research, build rapid AI-enabled prototypes, write production frontend code, evolve the design system, and partner with PMs, engineers, and analysts to deliver delightful, outcome-driven experiences for parents.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

Lead Registry product strategy and execution, own KPIs and commercial outcomes, manage a small PM team, champion AI-native product development, ship prototypes, run hypothesis-driven experiments, and raise the quality bar across acquisition, registry build, and shop funnels.