Sr. Product Engineer

Who we are

Help Scout started in 2011 with a simple premise: support software should treat customers like people, not tickets. 3+ billion conversations later, more than 10,000 companies use Help Scout to grow relationships with customers of all types, from clients to patients and beyond.

Now we’re in a new chapter: not only building AI that gives teams more space to focus on the customer experience, but also reimagining how we operate in an AI-native world. That means shipping and learning faster, without compromising on craft. Great work here carries a strong opinion and sweats the details, regardless of the tools we use to drive it.

We’ve been a fully remote team since day one, with 120+ teammates now all over the world. It’s a culture where you’ll be trusted to take ownership, stay curious, and raise the quality of work around you. It comes with clear expectations and a team that will push you to do some of the best work of your career.

If that kind of challenge gives you energy, we’d love to meet you.

About this role

This role sits on our Agents team — the group building the AI-powered experiences our customers use every day. It's where large language models stop being a demo and become a dependable part of the product: answers, drafts, and assistive features that have to be fast, trustworthy, and genuinely useful in front of real customers.

We're looking for an engineer who can build that end-to-end — from the retrieval and agentic plumbing behind a feature to the polished, fast, accessible interface a support agent actually touches. You'll have a frontend center of gravity (strong JavaScript/TypeScript and real front-end craft) while operating as a full-stack product engineer who owns the whole thing.

How we work

Engineers at Help Scout own their work end-to-end — from problem definition through production, and from the customer signal that shaped the bet to the dashboard that tells you whether it landed. You're full-stack capable, customer-fluent, and genuinely fast with AI tools. You ship the whole thing, not just your layer.

We develop in Kotlin, Java, TypeScript, React , and PHP.

We leverage Elasticsearch, ClickHouse, Kafka, Flink, RabbitMQ, MySQL, and PostgreSQL — plus vector search and LLM tooling for our AI features.

We're heavy users of the AWS ecosystem, Slack, GitHub, and Linear.

We use AI tools — Cursor, Claude Code, and a growing set of internal tools — every day. We treat our AI workflow as a product we're shaping together, and we expect you to help shape it.

Teams are small and project-based. You might be 3 engineers and a PM on one project, 2 engineers and a designer on the next, or holding more of the product thinking yourself. You're expected to operate well across different compositions and ship end-to-end.

What you'll do

Ship customer-facing AI features across the full stack. Build the experience and what's behind it — LLM-backed flows, retrieval (RAG) and embeddings, and agentic tool-calling — through to a fast, accessible, well-crafted UI. Most engineers here have a strength; yours leans frontend , and you take initiative across every layer.

Treat AI output as something you verify, not assume. Build evaluations, guardrails, and monitoring into AI features so quality is measurable and holds up in production. Know when to trust a model's output and when to push back — and design the system so the product degrades gracefully when a model or provider misbehaves.

Sweat the front-end craft. The interface is where AI either earns or loses customer trust. You care about responsiveness, streaming/loading states, accessibility, and the small details that make an assistive feature feel reliable rather than gimmicky.

Stay close to customers. Join customer calls when more context is needed to design the right solution, participate in a support escalation rotation, and watch session recordings on the features you own. Bring that signal back into the work.

Own outcomes, not just output. Before a project starts, you and a PM agree on a specific outcome metric the work is trying to move. You instrument it, and after it ships you're watching the dashboard and talking to customers — deciding what to do next, not just closing a Linear issue.

Co-author the solution. PMs own strategy and sequencing; you bring the judgment and craft for how solutions actually get built, and you'll often shape the product thinking too. The best work happens when engineers, designers, and PMs support each other.

Own production readiness from the start. Automation, reliability, monitoring, alerting, and logging aren't afterthoughts — they're part of how you ship. The work continues after merge.

Use AI tools every day as part of your craft. We expect fluency with Cursor, Claude Code, or similar. If you saw a way to make the team's AI workflow better tomorrow, you'd say so.