Principal Software Engineer, Enterprise Scalability

Klaviyo is a company that empowers creators to own their destiny by making first-party data accessible and actionable. They are seeking a Principal Software Engineer to lead enterprise scalability initiatives, focusing on performance, reliability, and large-tenant readiness while driving architectural changes and optimizing systems across teams.

Responsibilities:

• Define enterprise scalability fitness functions (latency/throughput/error rates) and a scorecard; align teams to SLOs and budgets
• Design/implement sharding and partitioning strategies, caching/back‑pressure, multi‑region readiness, and high‑volume migration paths
• Build lightweight enablement: benchmarks, profiling harnesses, reproducible testbeds; pair with teams to land fixes
• Lead scalability reviews and readiness gates that accelerate—not block—delivery; drive incident deep dives tied to systemic fixes
• Communicate clearly to execs and engineers, tying technical work to business impact and customer outcomes
• Integrate AI into scale and resiliency work—from proactive anomaly detection to synthetic load and guided runbooks—so performance improvements stick and incidents don’t repeat

Requirements:

• Experience: 12+ years scaling multi‑tenant SaaS with a reputation for removing major bottlenecks and proving impact with data
• Technical expertise: Performance engineering, capacity planning, sharding/partitioning, caching/back‑pressure, multi‑region readiness, and high‑volume migrations; you turn hotspots into robust patterns
• AI tools & automation: You apply AI to scale work—profiling assistance, workload modeling, synthetic traffic generation, anomaly detection, and runbook copilots—always with explicit guardrails and observability
• Cross‑org influence: You align teams through fitness functions, scorecards, and readiness gates that accelerate—not block—delivery; you communicate tradeoffs crisply to execs and engineers
• AI fluency: Curious, adaptable, and proactive in exploring AI that responsibly improves scale outcomes
• Scale scorecard: Company‑wide fitness functions (latency/throughput/error rates) are adopted and reviewed regularly
• High‑impact wins: 2–3 bottlenecks removed with documented, reproducible testbeds; pXX latencies and error rates improve on top enterprise workloads; repeat P0s trend down
• AI‑assisted scale engineering: AI‑driven anomaly detection reduces alert noise while improving signal; generative load testing and copilot runbooks are used in release/readiness checks for the top critical services; time‑to‑isolate regressions drops 20–30%