About The Position

Klaviyo is seeking a senior technical individual contributor to own its approach to enterprise scalability, performance, reliability, and multi-region readiness. Reporting to a VP of Engineering, this role has no direct reports and leads through technical expertise, hands-on engineering, and influence across teams. The engineer will identify and remove major bottlenecks, drive platform-wide architectural changes, and establish measurable readiness for Klaviyo’s largest tenants and most demanding workloads. Work spans system design, profiling, implementation, and production rollout. The role also helps teams adopt practical tools and repeatable patterns that make performance and reliability part of everyday engineering. It calls for an experienced engineer who can move between deep technical investigation and executive communication, make and defend architectural decisions, and build alignment across teams.

Requirements

  • 12+ years of relevant engineering experience, with a track record of removing significant bottlenecks and demonstrating measurable production impact.
  • Hands-on experience with performance engineering, capacity planning, sharding and partitioning, caching, back-pressure, tenant isolation, multi-region architectures, and large-scale migrations.
  • Ability to investigate unfamiliar systems, test hypotheses, write production code, and work with service owners to roll out changes safely.
  • Sound technical judgment in weighing architectural tradeoffs and deciding between immediate constraint fixes and broader platform changes.
  • Ability to align teams across organizational boundaries around shared outcomes and practical standards.
  • Ability to explain complex technical decisions and their business implications to engineering and executive audiences.
  • Experience applying AI tools or automation to engineering work and evaluating their usefulness, limitations, and operational risks.

Responsibilities

  • Define measurable scale-readiness targets for latency, throughput, error rates, and capacity; create a shared scorecard and align teams on service-level objectives, error budgets, and performance expectations.
  • Use production data, profiling, and reproducible benchmarks to identify important constraints; partner with service owners to implement fixes and verify improvements under representative workloads.
  • Design and implement sharding, partitioning, caching, back-pressure, and workload-isolation strategies; advance multi-region readiness and create safe paths for high-volume data migrations.
  • Create benchmarks, profiling harnesses, and test environments that teams can use independently, and help turn successful fixes into reusable patterns.
  • Lead scalability reviews and establish proportionate release gates that surface risks early.
  • Lead technical incident deep dives, identify systemic causes, and work with teams to deliver and validate fixes that reduce recurring incidents.
  • Apply AI-assisted profiling, workload modeling, synthetic traffic, anomaly detection, and guided runbooks where they improve engineering investigation and response; establish guardrails and measure operational impact.
  • Communicate priorities, tradeoffs, and results to engineers and executives, connecting technical investments to customer experience, enterprise growth, and operating efficiency.
  • Align teams around shared outcomes, clarify ownership, and build practical standards that help engineers move faster.
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