Staff Engineer, Applied AI (Customer Agent) at Klaviyo in Boston, MA

Job description

• 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.
• As a Staff 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-level 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.

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 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.
• 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.

Skills

Required

• Production agentic systems
• Orchestration
• Evaluation (evals)
• Guardrails
• Non-deterministic failure handling
• Securing agents against misuse and abuse
• Technical and product direction
• Hands-on coding
• Architecture design and review
• Debugging production issues
• Mentoring through design reviews
• Turning undefined problems into plans

Preferred

• 0-to-1 product development
• Startup environments
• Production evaluation systems
• AI observability

Benefits

• Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
• In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.
• Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
• $176,000—$264,000 USD