Note: The job is a remote job and is open to candidates in USA. Help Scout builds software for relationship businesses, and they are seeking a Staff Product Engineer to join their team. This role involves building AI-powered customer experiences and owning the full development lifecycle from problem definition through production.
Responsibilities
- 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
- Help us hire. From time to time, partner with our Talent team to interview future teammates — one of the highest-leverage things any engineer here does
Skills
- Strong, full-stack-capable engineer with a frontend center of gravity
- Substantial JavaScript/TypeScript and React experience
- Real front-end craft
- Initiative across the stack and ship end-to-end without waiting for someone to own the other half
- Built real things with LLMs — not just prototypes
- Comfortable with retrieval (RAG), embeddings, prompt/context engineering, and agentic/tool-calling patterns
- Point of view on what makes AI features actually reliable in production
- High bar for AI quality
- Think in terms of evaluation, verification, and guardrails
- Measure whether an AI feature works rather than assuming it does
- Genuinely fluent with AI coding tools and treat them as part of your craft
- Move fast without sacrificing judgment
- Customer-fluent
- Actively seek out customer signal
- Own outcomes
- Measure work by whether it landed
- Comfortable saying 'this didn't move what we hoped, here's what we want to try next,' then following through
- Take real ownership of the full development lifecycle
- Automation, reliability, resilience, monitoring, alerting, and logging built in from the start
- Stay with what you ship until the metric moves and the customer is better off
- Communicate clearly in writing and in conversation
- Give and receive direct feedback
- See code review and pairing as real chances to teach and learn
- Experience making LLM features production-grade: latency/cost tuning, fallbacks and circuit breakers across providers, moderation/safety, and handling sensitive data responsibly
- Familiarity with evaluation/observability tooling for AI (LLM-as-judge, test sets, tracing) and the discipline of building representative eval sets
- Design sensibility — comfort partnering closely with designers and elevating the craft of an interface, not just implementing a spec
- Experience in customer support, productivity, or other tools where trust and reliability are the product
Benefits
- Competitive salary and an internal, transparent salary formula based on market data
- Flexible time off – you choose the holidays and vacations that make sense for you
- 12 weeks of fully paid parental leave for all new parents, including adoption and foster care
- A home office stipend to help you get set up and productive
- A co-working stipend up to $300 a month if you choose to work out of your house
- A yearly professional development stipend of $1,800 to help you grow in your craft
- If you’re in the U.S. or Canada, we offer top tier health insurance for you and your dependents.
Company Overview