Software Engineer

What You'll Do

• Write high-quality, production-ready TypeScript code for our backend services and APIs
• Design, build, and maintain scalable services within our TypeScript monorepo
• Model data, design schemas, and optimize queries in PostgreSQL
• Integrate with external systems including HRIS platforms, ticketing systems, and third-party APIs
• Build infrastructure for AI-powered features—prompt engineering, context management, and reliable AI system integration
• Build for production with attention to observability, monitoring, and testability from day one
• Participate in design discussions, code reviews, and technical decision-making
• Collaborate closely with product, design, and engineering peers to deliver solutions that drive real business value

What We're Looking For

3+ years of professional software engineering experience, primarily in backend development
Strong proficiency in TypeScript or willingness to ramp quickly if coming from similar languages (Java, C#, Python)
Solid experience with relational databases—schema design, query writing, and performance basics
Familiarity with API design patterns and building services that other systems depend on
Ability to work effectively in ambiguity, prioritize well, and balance speed with maintainability
Strong communication skills and genuine interest in understanding the problems you're solving
Experience building AI-powered features or working with LLM APIs is a significant plus, though not required—this field is new enough that we're more interested in your curiosity and learning orientation than checking a box

Our Company Values

Our four values aren't aspirational. They translate into concrete operating tenets that shape how we make decisions every day.

 
• Beat Yesterday. We re-evaluate our own toolkit every quarter, because the workflows that made you effective three months ago may already be outdated. We act on 70% of the information rather than waiting for certainty. We timebox, execute, and iterate, getting work in front of real people quickly instead of polishing in isolation. And we own our output regardless of how we produced it. AI can get you 80% of the way there. Everything that goes out with your name on it is your responsibility to review, refine, and stand behind.
• Embrace Type 2 Fun. We take on hard problems and find meaning in the work, even when it's uncomfortable. We assume good intent and follow up directly rather than venting in side channels. We celebrate wins loudly and specifically, naming the actual behavior so the whole team learns what great looks like. We are on by default, because we owe it to each other and to our customers to be available beyond what a regular corporate job would demand. And we do unscalable things today that build scalable advantages tomorrow. Every white-glove dinner, every hand-built territory map, every late-night booth setup earns us the right to scale later.
• Stay Hungry, Stay Curious. We expect everyone to be the expert on AI in their function before anyone asks them to be. The landscape changes weekly. When you learn something, teach it. Learn enough about adjacent functions to ask good questions, including what your AEs are saying on calls, how brokers actually make money, and why a benefits committee pushes back on a deal. Ask the question you think is too basic, because in complex domains like benefits, the cost of a wrong assumption can be a lost account. And remember: curiosity without urgency is a hobby. Learning has to translate into action on a timeline that matches the opportunity.
• Act Like an Owner. We say the uncomfortable thing early, raising missed commitments or quality gaps directly with the person within 48 hours. We surface problems when they're small, not the week they become a crisis. Customer-facing work gets priority, always. And we close the loop every time, because over-communication is a feature at our stage, not a bug.