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San Francisco, California, United States
Onsite
At Lapel, we believe the most hospitable companies win. We're building the data, infrastructure, and tools that help customer-facing teams understand every customer and act on that insight at scale throughout the entire customer lifecycle.
Most internet businesses want to treat customers well, but their tools work against them. We’re building the layer that makes every interaction feel personal again: unifying context, coordinating action, and closing the gap between intent and experience.
It’s a technically ambitious challenge spanning data infrastructure, AI, and systems design – with a deeply human outcome: helping software companies serve people better. We call it hospitality at scale.
We’re well-funded, backed by top-tier investors, and already working with incredible companies, from fast-growing startups to large enterprises. We’ll share more details when we talk.
You’ll own the systems that power long-horizon agents at Lapel: how they remember, retrieve context, reason over customer history, use tools, take actions, and improve over time. This includes the memory, orchestration, observability, evaluations, and internal frameworks that make agents reliable across our products.
We believe that AI should be used to help scale the human moments and deliver exceptional service across any customer touchpoint. Your job is to build the infrastructure that makes that possible.
Design systems that help agents remember, summarize, and retrieve context across long-running customer interactions
Build workflows and tools that reduce failure modes and make agents easier to trust in production
Set up the observability and eval infrastructure we use to monitor agent behavior, debug issues, and raise quality over time
Help to scale multi-tenant systems that keep customer and agent context isolated, reliable, and ready for enterprise use
Lapel is built end-to-end in TypeScript in a single monorepo.
React, Vite, and Tailwind on the frontend;
Node.js and Postgres on the backend;
Temporal and Pulsar to power orchestration.
We ship quickly, and care about creating a developer experience where anyone can prototype, experiment, and get ideas into production fast.
Have 5+ years of backend or software engineering experience, with a track record of building reliable systems in production
Have owned large-scale, enterprise products end-to-end
Are excited to build the systems that make AI agents more useful, dependable, and easier to improve
Are comfortable designing APIs, working with databases, and building workflows that run reliably over time
Understand system design, debugging, observability, and production reliability at a practical level
Are customer-focused and able to translate product needs into reliable agent infrastructure
Enjoy working in fast-paced environments with high ownership and autonomy
Are proactive, detail-oriented, and take pride in building high-quality systems
We aim to hire with intention, respect your time, and offer feedback along the way.
Initial conversation (20 minutes) We’ll explore your motivations, share what we’re building, and answer your questions.
In-depth interview (45 minutes) We’ll go deeper into your craft and experience. No live coding. No prep work necessary.
Take-home project (2–4 hours) You’ll complete a short, well-scoped exercise that mirrors the kind of work you’d do here.
On-site visit (1–2 days) Join us in the office to review your take-home, grab lunch, and work on something real.
We believe great people build great companies – and we invest accordingly.
Competitive salary + meaningful early-stage equity
Full benefits: medical, dental, vision, 401(k), and commuter benefits
Generous time off: many company holidays and coordinated team-wide breaks throughout the year to focus and recharge
Office perks: lunch and dinner provided daily, in-office snacks, and health & wellness benefits
Team culture: regular off-sites, tight feedback loops, and a bias toward action
A trillion-dollar problem hiding in plain sight. Companies spend over $1T a year on customer-facing teams and $150B on the tools meant to support them, yet every team still pieces context together across a dozen disconnected systems. We're rebuilding this from the foundation, and AI makes now the only moment it's possible.
The most interesting place to apply AI is where the work actually happens. Customer operations is one of the largest, most under-built surfaces in software. Every company runs on it, every team feels the pain, and the tools haven't been seriously reimagined in fifteen years. We think the next generation of category-defining B2B companies will be built here.
One platform, every customer-facing team. Sales, success, support, and ops all serve the same customer relationship, but each one buys a different tool to do it. Owning the foundation means the surface area grows with the company, from a single team to the entire revenue org to the whole business. That's the market, and the mission: better service at internet scale.
Lapel works in person in San Francisco, five days a week, at our office on Market Street. We hire people who'd be restless anywhere else.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristics.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
