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Be Klaviyo’s senior IC for scale, you will report into a VP of Engineering and lead performance, reliability, multi‑region, and large‑tenant readiness. You’ll drive platform-wide architectural change, hunt bottlenecks and optimize systems, and partner across teams to productionize improvements. Given that this is an IC role with no direct reports; you will lead via technical depth, hands‑on impact, and crisp cross‑org alignment.
What You’ll Do
- 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.
Who You Are
- 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.
Nice to Haves
- 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