Babylist is the best baby registry for growing families. Add baby gear from any store including Amazon, Target, and Etsy. Start building your registry today! Backed by Norwest and 500 Global.
About the role
Babylist's Platform team is the foundation every engineering team builds on — and this role is at the center of keeping it reliable, fast, and scalable. As a Staff SRE, you'll own the infrastructure and reliability practices that support 9 million+ users and the engineers who build for them. Babylist started as an e-commerce and registry platform, and we're actively growing beyond that — into health, media, mobile, and new product surfaces that don't exist yet.
What they're looking for
- Deep hands-on Terraform expertise — you own IaC, not just contribute to it
- Proven AWS experience at scale — EKS, RDS, cloud networking, DNS, CDNs, load balancers — you know the gotchas
- Experienced operating Kubernetes in production — you've debugged the hard stuff, not just deployed the easy stuff
- Comfortable designing and improving CI/CD systems — CircleCI, GitHub Actions, or similar, you care about developer velocity, not just pipeline uptime
- Strong observability instincts — Datadog, Sentry, PagerDuty, Cronitor — you build alerting that's actionable, not noisy
- Experienced with on-call and incident management — you've run the post-mortems and actually changed things afterward
More about this role
How We Build
Babylist is in the middle of a fundamental shift in how software gets made, and we are not tiptoeing into it. We are rebuilding our engineering culture around a simple belief: AI changes everything. How teams are structured, how decisions get made, how fast ideas become working software. Our engineers own problems end to end, working directly with product, design, and business partners with short feedback loops and real stakeholder access. We ship, learn, and iterate fast. When something is not working, we throw it out and start over — project failure and personal failure are not the same thing here. AI tools are as natural to our workflow as an IDE or version control. We are not exploring this, we are living it. Our engineers use AI to explore tradeoffs, pressure-test designs, and move from problem to solution in hours instead of days. They generate code with AI so they can stay focused on the decisions that actually require human judgment — not the routine ones. More velocity means more time for craft: better test coverage, stronger architecture, and deeper customer understanding. We hold ourselves to a higher quality bar because of AI, not in spite of it. We are...
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