Principal Engineer, Enterprise Scalability
Klaviyo · Boston, MA
About this role
## Principal Engineer, Enterprise Scalability *At Klaviyo, we value the unique backgrounds, experiences, and perspectives each Klaviyo brings to our workplace. If you’re a close (but not exact) match, we encourage you to apply.* --- ### Your Impact We’re seeking a senior technical leader to own Klaviyo’s approach to **enterprise scalability, performance, reliability, and multi-region readiness**. Reporting to a **VP of Engineering**, you’ll be a **senior individual contributor (no direct reports)**—leading through technical expertise, hands-on engineering, and cross-team influence. You’ll: - Identify and remove major bottlenecks - Drive platform-wide architectural changes - Establish clear readiness measures for our largest tenants and most demanding workloads - Span system design, profiling, implementation, and production rollout - Help teams adopt practical tools and repeatable patterns so performance/reliability become everyday engineering --- ### What You’ll Do - **Define what scale readiness means**: Set measurable targets for latency, throughput, error rates, and capacity; build a shared scorecard and align on SLOs, error budgets, and performance expectations. - **Remove the bottlenecks that matter most**: Use production data, profiling, and reproducible benchmarks; partner with service owners to implement and verify fixes. - **Drive architectural change**: Design/implement sharding, partitioning, caching, back-pressure, and workload isolation; advance multi-region readiness and enable safe high-volume migrations. - **Make scale engineering repeatable**: Create lightweight benchmarks, profiling harnesses, and test environments; turn successful fixes into reusable patterns. - **Build readiness into delivery**: Lead scalability reviews and establish proportionate release gates that surface risks early. - **Turn incidents into lasting improvements**: Lead deep dives, identify systemic causes, and deliver validated fixes that reduce recurring incidents. - **Apply AI where it improves outcomes**: Use AI-assisted profiling, workload modeling, synthetic traffic, anomaly detection, and guided runbooks—with guardrails, evaluation, and measured operational impact. - **Connect engineering decisions to customer needs**: Communicate priorities, tradeoffs, and results clearly to engineers and executives. --- ### What You’ll Bring - **12+ years scaling multi-tenant SaaS experience**, with a track record of removing significant bottlenecks and delivering measurable production impact - **Strong performance + distributed systems expertise** (performance engineering, capacity planning, sharding/partitioning, caching, back-pressure, tenant isolation, multi-region architectures, large-scale migrations) - **Engineering depth from diagnosis through delivery** (investigate unfamiliar systems, test hypotheses, write production code, roll out safely with service owners) - **Sound technical judgment** (use evidence to weigh tradeoffs; decide when to address immediate constraints vs. invest in broader platform change) - **Leadership across organizational boundaries** (align teams around shared outcomes; clarify ownership; build practical standards) - **Clear communication** to both engineering and executive audiences - **Practical AI fluency** (apply AI tools/automation responsibly; evaluate usefulness, limitations, and operational risks) --- ### Success in 6–12 Months - A company-wide **scale scorecard** is adopted and regularly reviewed with agre
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