Lead Engineer - Applied AI, Customer Agent

Lead Engineer, Applied AI (Customer Agent)

About the Team:

Our Engineering team builds the AI systems that power how brands run their businesses on Klaviyo. We move fast, ship in production, and hold a high bar for what "AI-native" actually means: systems that make real judgment calls, not demos.

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. We're still small enough that one engineer’s work visibly shapes how the whole platform evolves. We're past the demo stage: the team ships changes against live customer traffic, measures quality with real evaluation frameworks, and treats reliability as a product feature, not an afterthought.

About the Role:

As Lead Engineer, you'll set the technical and product direction for a core area of Customer Agent end to end, building a 0-to-1 agentic product with the speed and ownership of a startup, backed by the scale and resources of one of the most innovative tech companies on the East Coast, while staying hands-on with the hardest problems yourself. This is a lead role, with a wide footprint across our agentic product - from orchestration to governance - that grows based on where the product is when you join. We're looking for an engineer who owns complex, ambiguous problems, who has built, scaled, and supported a production agentic system through everything that comes after the demo, and who up-levels the people, process, and technology around them.

How You'll Make an Impact:

• 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.

What We're Looking For:

• You've built, scaled, and supported production agentic systems, not just prototyped them: real orchestration, evals, guardrails, and non-deterministic failure handling. You've owned your part of one through launch, incidents, and the operational reality after the demo.

• 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, and you can point to something you designed and championed that shipped and that other engineers built on.

• You're hands-on: writing code, reviewing your own and others’ architecture decisions, and debugging production issues yourself, not delegating the hardest problems away.

• Your patterns and designs are reused by other engineers, and you've unblocked many others’ projects, not just your own.

• You communicate complex technical trade-offs clearly across engineering and product audiences, and you can turn an undefined problem into a plan others rally behind.

Nice to Haves:

• Experience working on a multi-tenant agent platform at production scale, where external customers configure their own agent behavior on shared infrastructure.

• 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.

Boston, MA - In-Office Role