Associate Software Engineer
Employees are confused about their benefits, and the leaders funding that second-largest expense often can't tell what's working. Avante is changing that: We're an AI-native benefits intelligence platform already trusted by brands like Samsung, News Corp, and Zscaler, with two purpose-built agents. Carly gives employees personalized, always-on guidance, and Ava gives benefits leaders analyst-grade answers on cost, utilization, and outcomes in seconds, closing the loop between employee experience and strategy.
The Role
As an Associate Software Engineer at Avante, you will write production code with guidance and support from senior teammates while building hands-on fluency with the AI-native tools and workflows central to how we build. This is a growth-oriented role designed for early-career engineers who have already shown genuine technical curiosity, particularly around AI. You will take on real ownership from day one, backed by the mentorship and code review needed to develop quickly.
What You'll Do
AI-Native Engineering
- Get hands-on with the AI infrastructure behind Carly and Ava, including prompt engineering, context management, and agent-assisted development. This is a core part of how you build, not a separate skill to pick up later
- Use AI coding tools day to day as part of how you write and ship code, not as an occasional add-on
- Grow your judgment about when to write code directly versus guide an AI agent to do it
Product & Customer Impact
- Collaborate with product, design, and engineering peers, and build your own product and customer intuition along the way
- Participate in design discussions and code reviews
Ownership & Execution
- Write clean, well-tested TypeScript code for our backend services and APIs, with support and code review from senior teammates
- Contribute to the design and maintenance of services within our TypeScript monorepo
- Help model data, design schemas, and write queries in PostgreSQL
- Work with existing integrations to external systems such as HRIS platforms and third-party APIs
- Build for production with growing attention to observability, monitoring, and testability
What We're Looking For
- 1-3 years of professional software engineering experience, or equivalent hands-on project or internship experience with a strong technical foundation
- Working proficiency in TypeScript or a similar language (Java, C#, Python), with a demonstrated ability to learn quickly
- Foundational understanding of relational databases, including schema design and query writing
- Genuine, self-directed engagement with AI tools. Personal projects, coursework, or independent exploration count as much as on-the-job experience, and we care more about your curiosity and pace of learning than your years of production exposure
- Early signs of product and customer judgment: you can explain the "why" behind a technical decision, not just the "how"
- Comfort working in ambiguity and eagerness to take ownership of problems beyond your assigned scope
- Strong communication skills and a genuine interest in understanding the problems you're solving
- Initial screen with a member of our recruiting team
- Video Interview with our Engineering Manager
- Technical interview focused on real-world problem solving (no whiteboard algorithms)
- On-site interview loop:
- Team behavioral interview (60 min)
- Session with our Engineering Manager (60 min)
- Final conversation with our CTO (30 min)
How We Work
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 hand-built account play and late-night proposal turnaround 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. 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.
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