Who We Are Babylist is the leading platform for expecting and new families. More than 10 million people shop with Babylist every year, making it the go-to destination for seamless purchasing, guidance, and expert recommendations. As a modern, AI-forward tech company, Babylist has expanded from a universal registry into a full ecosystem — the Babylist Shop, Babylist Health, Babylist Money, NYC and LA showrooms, branded content, and more — generating $750M in revenue in 2025. Building the generational brand in baby, Babylist is reshaping the $235B kids and baby market and helping parents feel confident, connected, and cared for at every step. Our Ways of Working Babylist is remote-first with team members across the U.S. and Canada who move fast, think smart, and use AI as part of how they work every day — not as an experiment, as an expectation. We come together twice a year to build the relationships behind the work, and we hire people who are genuinely excited about what's possible and prove it through how they show up. What the Role Is The Data team at Babylist powers decision-making across the entire business — from product growth to operations to AI. This is a senior individual contributor role on the Data Engineering team, sitting at the intersection of platform thinking and AI-native tooling. You'll own the architecture and systems that make data engineering itself more scalable — not just the pipelines, but the harnesses and agentic scaffolding that generate, test, and maintain them. You'll work cross-functionally with analysts, data scientists, and product teams to keep Babylist's data infrastructure reliable and ahead of where the business is going. Who You Are - Experienced building production AI/LLM systems — RAG pipelines, agentic workflows, tool integrations (e.g., MCP servers) that real users depend on, not just prototypes - Platform-minded — you see repetitive data engineering work as a system design problem and build the scaffolding to automate it - Deeply fluent in Python and production-grade data engineering, with 7+ years building systems that hold up at scale - Proficient with Airflow and dbt — you understand data modeling and ETL principles, not just the tooling - Comfortable in AWS — you've provisioned and managed cloud data resources across EC2, S3, Lambda, and EKS - Familiar with Snowflake or comparable modern cloud data warehouses - Able to work cross-functionally with analysts and data scientists — translating their needs into infrastructure that actually serves them - You naturally reach for AI in your work — at Babylist, every team uses AI daily. You're already using it to move faster and improve your output, and you stay curious about what's coming next. - You're genuinely excited about what AI can do - not just as a concept, but as something you want to get your hands on. At Babylist, every team uses AI daily, and we're looking for people who lean in. How You Will Make An Impact - Build and scale data pipelines for ingestion into Snowflake — with a focus on reliability and performance across a $750M+ e-commerce business - Design and ship the agentic systems that perform data engineering work — pipeline generation, testing, and maintenance as automated systems, not one-off builds - Develop and maintain ML pipelines that help data scientists operationalize models and integrate them with our data infrastructure - Implement and improve data monitoring across complex, multi-system user journeys - Collaborate with Analytics Engineers on data modeling and the reliability of shared data assets - Partner with product, analyst, and ML teams to deliver end-to-end data solutions — from ingestion to advanced analytics and AI\ Why This Role - You're building the meta-layer — not just pipelines, but the systems that build pipelines; it's a rare scope for a data engineering role - The data infrastructure is solid; you're extending and automating something that works, not inheriting a mess - AI is core to the mandate here, not a future aspiration — agentic data engineering is a real part of the roadmap, not a stretch goal - You'll have direct influence on how a 9M+ user platform scales its data systems through a pre-IPO growth moment. About Compensation We use a market-based approach to compensation. The starting salary range for this role is: $186,086.000 to $221,800 Your starting salary will be based on your location, experience, and qualifications, with increases over time tied to performance, role growth, and internal pay equity. Why You Will Love Working At Babylist Our Culture - We work with focus and intention, then step away to recharge - We believe in exceptional management and invest in tools and opportunities to connect with colleagues - We build products that positively impact millions of people's lives - AI is intentionally embedded in how we work, create, and scale—supporting innovation and impact Growth & Development - Competitive pay and meaningful opportunities for career advancement - We believe technology and data can solve hard problems - We're committed to career progression and performance-based advancement Compensation & Benefits - Competitive salary with equity and bonus opportunities - Company-paid medical, dental, and vision insurance - Retirement savings plan with company matching and flexible spending accounts - Generous paid parental leave and PTO - Remote work stipend to set up your office - Perks for physical, mental, and emotional health, parenting, childcare, and financial planning Important NoticesRecorded Interviews. Babylist uses an interview recording tool to record and transcribe interviews for evaluation purposes in accordance with applicable privacy laws. By participating in an interview, you consent to this recording and transcription. Interview Integrity. AI is part of how we work at Babylist — we expect you to use it too. Your application and interviews should still reflect you and your own thinking. We'll tell you when AI is encouraged. Misrepresentation at any stage may result in removal from consideration for this and future roles. Connections at Babylist. If you have a family member or close personal relationship with a current Babylist employee, please let your recruiter know. This helps us keep our process fair and transparent for everyone. Protect Yourself from Scams. All official outreach comes from the Babylist Talent Team via @babylist.com email addresses only. We will never ask for payment or personal financial information. If you receive outreach via WhatsApp, Telegram, or a non-Babylist email — it's not us. Verify open roles at babylist.com/careers.

• Architect and build scalable, secure, and observable data infrastructure to power LLM-based agents, multi-agent systems, and tool-using AI workflows. • Design and operate robust batch and real-time data pipelines supporting embeddings, RAG systems, and agent memory frameworks. • Develop and manage vector database solutions to enable low-latency retrieval and contextual intelligence for AI applications. • Build data frameworks for training, evaluation, benchmarking, and continuous improvement of agentic AI systems. • Implement strong data governance, quality controls, lineage tracking, and PII/security compliance across AI data platforms. • Collaborate with AI/ML, platform, and DevOps teams to productionize experimental AI prototypes into enterprise-grade solutions. • Optimize data systems for performance, scalability, reliability, and cost efficiency across cloud environments (AWS, Azure, or GCP).

• Serve as the Owner's architectural SME and trusted advisor throughout planning, design, construction, and project execution phases. • Partner with internal stakeholder teams, design consultants, construction management firms, and general contractors to administer design documentation and ensure compliance with Owner standards and project objectives. • Provide technical direction and comprehensive reviews of architectural design packages with a focus on life safety and egress requirements, ADA compliance, signage programs, site planning, and core data center building design. • Develop, maintain, and enhance architectural design standards, campus planning guidelines, and prototype building templates to support consistency and scalability across projects. • Lead technical reviews of consultant deliverables at key design milestones, providing detailed peer-review feedback on Basis of Design (BOD) documents and 30%, 65%, and 100% construction documentation packages.

• Join a small, collaborative team defining questions for user research and experimenting with internal data. • Engage with internal and external users, and be involved in all phases of product development. • Work with Python, Databricks, Postgres, and occasional SQL to develop deep knowledge of the data in our catalogue. • Help set priorities for new data sources and partner with a data scientist and another software engineer for data transformations. • Collaborate closely with platform teams and write requirements docs and proposals.