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Salary
$101k – $255k per year (Estimated)
Location
In office
Seniority
Senior · 6+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Lemonade sells renters, home, pet and car insurance through a chat-driven app. Artificial intelligence handles quoting and a large share of claim payments instantly. The company donates unclaimed premium to causes chosen by policyholders.

What you're applying for

Anyone can ship an AI agent. Shipping one that’s right ~98% of the time, with no human checking its work, takes different engineering. That’s what this team builds.

We're looking for a Senior Backend Engineer to help push our AI customer-service agents closer to fully autonomous insurance service. You'd be joining the team behind the agent that talks to real customers every day over email, phone, chat, and SMS - handling policy questions, claims conversations, and verified documents end-to-end, with no human in the loop. This isn't a demo or a copilot. Real customers, real money, real stakes, every day.

We believe three things matter for every role at Lemonade: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.

Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.

In this role you'll

  • Design, build, and own production LLM agent systems end-to-end - deciding how the agent thinks, what it's allowed to do, and how it fails safely

  • Work on our real-time voice agent, where the hard problems are conversational: interruptions, mid-sentence tool calls, and keeping response times imperceptibly fast

  • Shape the next generation of our knowledge base - how the agent's knowledge is structured, curated, and served, so answers stay grounded as coverage grows

  • Ship changes as controlled experiments, measure them against thousands of replayed real conversations on our in-house eval platform, and graduate winners into production

  • Track cost per conversation across millions of LLM calls and find the wins that cut spend without cutting quality

  • Own what the model knows and says - the customer context it sees, the limits on what it may reveal, and the guardrails against confident nonsense

  • Build and operate scalable backend services in TypeScript/Node on Kubernetes/AWS with deep observability - if you ship it, you own it

What you'll need

  • 6+ years building production-grade backend systems that real users depend on

  • Hands-on experience shipping LLM-powered features to production, including honest reckoning with non-determinism, hallucination, and cost

  • An evaluation mindset - you don't call a change "better" without a measurement, and you're comfortable with the statistics that back that claim

  • A track record of debugging distributed systems in production, and the discipline to find root cause across service boundaries

  • Fluency with agentic coding tools like Claude Code or Cursor, including the habit of treating AI-generated code with a senior reviewer's skepticism

  • The ability to pull your own numbers, design your own experiments, and measure your own impact

  • Ready to work in an office environment most days of the week

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