About the company
Klaviyo values the unique backgrounds, experiences and perspectives each Klaviyo brings to our workplace. Our Engineering team builds the AI systems that power how brands run their businesses on Klaviyo.
About the team
The Customer Agent team is one of the newest and most ambitious groups in that org, based in Boston and working in-office: we're building a conversational AI system that lets brands serve their own customers at a scale no human support team could match.
Responsibilities
- Set the technical and product direction for a core area of Customer Agent, from architecture through production, and contribute to the direction of the platform overall.
- Take on the hardest technical problems in your area: orchestration, evaluation, guardrails, memory & context, failure handling for non-deterministic systems.
- Write and ship code, review designs, and make the hard calls in your area when there’s no obvious right answer.
- Define patterns that other engineers adopt, and mentor through design reviews rather than direct management.
- Partner with product, design, data science, and go-to-market leaders to shape what gets built, not just how it’s built.
- Evaluate emerging AI technologies and bring the ones worth betting on into production.
Requirements
- You've built, scaled, and supported production agentic systems, not just prototyped them: real orchestration, evals, guardrails, and non-deterministic failure handling.
- You've learned the hard lessons that only come from running agents in production: securing them against misuse and abuse, and the operational scar tissue of keeping a non-deterministic system reliable as usage grows.
- You've owned technical and product direction for a significant area before, not just your own component.
- You're hands-on: writing code, reviewing your own and others’ architecture decisions, and debugging production issues yourself.
- Your patterns and designs are reused by other engineers, and you've unblocked many others’ projects.
- You communicate complex technical trade-offs clearly across engineering and product audiences.
Nice to have
- Experience working on a multi-tenant agent platform at production scale.
- Experience building 0-to-1 products or working in startup environments.
- A track record with production evaluation systems, AI observability, or human-in-the-loop workflows for LLM-powered products.
Conditions
- Boston, MA - In-Office Role.
- Base Pay Range For US Locations: $176,000 — $264,000 USD.
- This role may require up to 10% travel.