Babylist
From Babylist's careers page
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What The Role Is As a Staff Engineer at Babylist, you own some of our hardest domains and decide where they go.
What The Role Is
As a Staff Engineer at Babylist, you own some of our hardest domains and decide where they go. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person. We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families.
You'll own a big piece of the product, but you won't be boxed into it. The roadmap is open. You have a say in which bets we make, and you pick what you take on next.
A Staff Engineer here sets direction. You own a domain: a product surface, a platform area or a capability that cuts across several teams. You set where it's going over the next year or two, sequence the bets that get there and make the technical and product calls along the way. You're still in the code. We don't have architects who've stopped building. If you stepped away, multiple teams would feel it. Your influence shows up in the systems and the work other teams choose to build on. You don't need direct reports to have that reach. It comes from what you build.
Take a fuzzy business problem from the first sketch through to production, and stay on the hook for whether it actually helped customers.
Build the platform or tooling other teams adopt by choice, and own it as it scales.
Make the architecture calls that span teams and the ones that are expensive to reverse.
Set the standard for how your domain builds with AI. Decide what good looks like, build the patterns and evals that get agents there and catch the output that's confidently wrong before it ships.
Partner with product, design and data as a peer, shaping what's worth building from the start.
Coach Senior engineers through the hard calls, the ambiguous ones as much as the technical ones.
Resolving one customer across registry, shop and health, plus the friends and family buying for them, so personalization works everywhere without each team rebuilding it.
Designing the knowledge system our coding agents reliably load, and working out how much context actually helps before it starts to hurt.
Building Early Investor, our new family finance product, from scratch, on a deadline that can't move.
You've shipped production systems for enough years to have earned strong opinions, and you hold them loosely. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. You've already changed how a team builds with AI, and the new way stuck. Most Staff engineers lean one of two ways, and both do well here. Some point their depth at the systems everyone runs on: the platforms, the reliability and security bar, the harnesses that make AI produce good code. Others point it at the customer: framing the problem with PMs as peers, owning a journey end to end, deciding what to build and learning whether it worked. You don't have to be both. You do have to be excellent at one and fluent in the other.
You measure yourself by impact: a customer outcome, or a system a dozen teams come to depend on.
You're curious: you spot problems before they're filed and push your own ideas until they ship.
We post real numbers. For a US-based Staff Engineer, the starting base salary range is $233,500 to $290,700, plus a target annual bonus of 20 percent of base. That's total target cash of roughly $280,200 to $348,840. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome.
The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app: Rails, Packwerk, React, TypeScript, Sidekiq
Mobile: iOS (Swift), Android (Kotlin)
Data, search & events: MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning: deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling: Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops: AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks start to finish.
Recruiter conversation (30 minutes). Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour). One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours). Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address
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