Jobs / Canada / Babylist INC

Babylist INC

Senior Software Engineer

Canada Posted 1 month ago $255,900

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Product managementTriageRubyMySQLReactTypeScriptiOSSwiftAndroidKotlinSnowflakedbt

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Sponsorship verdict

No sponsorship evidence yet

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No salary bar for this route
Canada has no single salary bar: the employer usually needs a positive LMIA. Pay at or above the provincial median wage + 20% (e.g. C$36.92/h in Ontario) puts it in the high-wage stream. Source: https://www.canada.ca/en/employment-social-development/services/foreign-workers/median-wage.html, rules effective 2026-07-17.

Canada: Express Entry no longer awards ranking points for job offers (since 25 Mar 2025); a job offer still counts toward Federal Skilled Worker eligibility.

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Sponsorship unknown

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About the role

What The Role Is As a Senior Engineer at Babylist, you take on hard problems and own them end-to-end. 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 start on a team, but you won't be boxed into it. The roadmap is open, your scope grows as you do and you have a say in what you take on next. Senior here means owning whole problems; Staff is the next step up, setting direction across a domain. What You'll Own A Senior Engineer here owns problems, not just features. You're handed an outcome, you decide what to build, ship it and own whether it worked. You act on incomplete information and change course fast when the evidence says you were wrong. What you do depends on what the team needs: • Frame the problem with your PM as a peer, run the experiment and bring customer evidence into what gets built. • Harden a critical path, kill a class of incidents or design the abstraction your team builds on. • Be the reviewer people want on the risky changes. • Manage up with crisp choices: raise the risks early and protect the right tradeoffs. • Share what you're learning about AI openly, so the whole team gets sharper. A few problems people at this level are working on right now: • Deciding what the registry recommends to each family, from the ranking to the model behind it, and proving in a live experiment that it actually helps. • Building the evals system that catches our AI support agent making things up before a customer does. • Making a child's info one source of truth instead of five disconnected flows, so parents set it up once and new products like Early Investor build on it. Who You Are You've been shipping production systems for years, and you've got the judgment to show for it. You can pick up an ambiguous problem and start moving before anyone hands you the full picture. The strongest Senior engineers here are generalists, and usually the most prolific builders on their team. You go wherever the problem leads: a backend service one week, a stubborn frontend bug the next, the data pipeline after that. When it's hard you dig in, and you learn unfamiliar parts of the stack fast. Range is the Senior signature. Compensation We post real numbers. For a Canada-based Senior Engineer, the starting base salary range is $255,900 to $318,600 CAD, plus a target annual bonus of 15 percent of base. That's total target cash of roughly $294,285 to $366,390 CAD. On top of that you get meaningful equity and an RRSP 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 ap

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