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Salary
≈ $180k – $329k per year (Estimated)
Location
Hybrid (New York, San Francisco, United States)
Seniority
Staff · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on May 5, 2026. Sei scores B on the Alion truth index.

Overview
Company
Impact
Profile match

Sei

Sei is a blockchain project founded in 2022 that optimises its base layer specifically for trading applications. It includes parallel execution and order matching directly in the protocol to reduce latency for exchanges built on top of it. The network has since adopted Ethereum Virtual Machine compatibility to broaden its developer base.

About Sei Labs

Sei Labs builds open sourced technology for the high-performance Sei Blockchain, the first parallelized EVM Layer 1 blockchain designed to scale with the industry. The unique optimizations built into Sei enable Web3 applications to reach Web2 level scale and performance, driving the mass adoption of digital assets.

Our teams are comprised of former Google, Goldman Sachs, Robinhood, Nvidia, and Databricks veterans dedicated to onboarding the next billion users onto a vibrant ecosystem of applications.

Sei Labs has raised over $30M from top investors including Jump Crypto, Multicoin Capital, Coinbase Ventures, Distributed Global, Hudson River Trading, and Flow Traders.

Check out our website and docs for more details.

Platform Engineering at Sei

We're building Sei into a world-class L1 for decentralized finance. This role exists to make the safe path the default path for every engineer on the team - observable, tested, reversible, and fast. You'll be a foundational hire on a small Platform Engineering team with a broad mandate.

What you'll own

  • Infrastructure & scale testing. Build and maintain Docker/Kubernetes harnesses for repeatable stress and scale testing, used by every core team as a pre-release gate. Run our multi-cloud footprint with explicit reliability and cost targets.

  • Release engineering & CI/CD. Consolidate CI/CD into reusable, standardized workflows. Own version tagging, hotfix paths, PR review scaffolding, and the full release lifecycle.

  • Observability. Single pane of glass for metrics, traces, and logs - correlated by block height, powered by OpenTelemetry. HA Prometheus, ELK, defined SLOs on every critical service.

  • Performance & chaos testing in CI. Automated chaos and performance tests gating 100% of releases. Regressions caught before merge, not by users.

  • Security & incident response. Run the bug and vulnerability workflow end to end - auditors, Immunefi, triage, postmortems. Every incident produces a new test, metric, or runbook.

What we're looking for

  • 5+ years building production systems at scale. You've designed and shipped infrastructure that other engineers rely on, and you understand it end to end - not just the surface API.

  • Security fundamentals. Threat modeling, common vulnerability classes, and how security work integrates into a development pipeline. You don't treat audits as a checkbox.

  • Distributed consensus understanding. You can reason about consensus protocols at the algorithmic level - safety vs. liveness, fault assumptions, the failure modes that show up in practice. You've debugged something non-trivial at this layer or studied it deeply enough to.

  • Benchmarking & performance bottleneck analysis. You design benchmarks that isolate variables. You profile under realistic load. You can walk into an unfamiliar system, find the bottleneck, and explain why it's the bottleneck before proposing a fix.

  • Live incident response. You've operated systems where outages had real consequences. You triage under pressure, communicate clearly, and turn postmortems into structural fixes that don't quietly expire.

  • End-to-end systems thinking. You've built systems, not just glued tools together. You have opinions on monitoring stacks, what belongs in CI vs. CD vs. runtime, and when to reach for chaos testing - and you can defend them.

Bonus

  • Blockchain or web3 infrastructure experience, especially with consensus, mempool, or storage layers.

  • Multi-cloud cost programs that didn't compromise reliability.

  • Experience integrating AI-assisted security tooling into a development pipeline.

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