Backend Team

Nanit is moving families beyond overwhelm by transforming how parents understand their baby's early years. We combine advanced AI, real-world data from billions of sleep hours, and clinical expertise to deliver the clarity and confidence every parent deserves. Trusted by over one million families and backed by $125M in funding, we're building an entirely new category: predictive parenting intelligence.

Here, your work directly impacts millions of families. Our team of scientists, engineers, and parents is small but mighty - we share a mission to make early childhood easier, healthier, and more connected. If you want to work on technology that genuinely matters, join us.

As a Backend Team Leader at Nanit, you will lead a team of backend and MLOps engineers that owns the systems behind our AI-driven product features. Your team works closest to our AI group - the Algorithms and Data teams - and owns the engineering side of turning models into reliable production capabilities.

Concretely, that means owning real backend architecture - the services and APIs that carry AI-driven capabilities into the product, the data collection pipelines that feed model training, the storage and query layers that hold model outputs and the insights we derive from them, and the validation pipelines that let us trust production flows. You will make the core design decisions on service boundaries, data models, event flows, and scale and cost tradeoffs, in a domain where both the data volume and the correctness bar are high. You do not need to arrive as an ML expert. You do need to be the kind of engineer who walks into an unfamiliar domain, learns it properly, and starts making good decisions in it.

What you'll be doing - 

Lead and grow the team

• Manage backend and MLOps engineers, some embedded in product pods; coach on delivery, decision-making, and career growth
• Set clear expectations for ownership and quality; track progress against team goals, surfacing risks early

Own the backend behind our AI features

• Build and scale data pipelines with the AI group, and design how model insights are stored, queried, and exposed to the product
• Build validation pipelines and partner with the Algo team to take models from experiment to production

Drive architecture direction and alignment

• Align backend decisions with the wider group, guide design discussions, and keep specs and plans on time
• Collaborate with the platform team on infrastructure, deployment, and reliability standards

Improve reliability and operational readiness

• Raise the bar on stability, observability, and alert quality