Senior Distributed Systems Engineer

Details

• Design, build, and operate backend services that enforce regional boundaries on where customer data is stored, processed, and decrypted, across a globally distributed edge network.
• Contribute to end-to-end feature delivery — write technical designs and RFCs, implement services and libraries, add tests and observability, drive rollout, and own the resulting systems in production.
• Partner with engineers on adjacent platforms, cryptography, networking, data, and product teams to integrate residency guarantees into new and existing surfaces without regressing performance or reliability for other customers.
• Reason carefully about failure modes, consistency, and blast radius; design systems that fail closed for compliance while degrading gracefully for availability, and make these tradeoffs explicit in design docs.
• Participate in on-call for your services, lead incident response and post-mortems, and continually invest in reliability, capacity planning, and cost.
• Raise the engineering bar through code review, mentorship, and clear written communication; contribute to the team's engineering standards and tooling.
• 5+ years of professional experience designing, building, and operating production distributed systems at scale.
• Strong proficiency in at least one system or backend language such as Go, Rust, or C/C++, and a willingness to work in others as the codebase demands.
• Solid grasp of distributed systems fundamentals, including:
• Consistency and consensus models (strong, sequential, eventual; Paxos / Raft at a conceptual level).
• Replication, sharding, and partitioning strategies, and their tradeoffs against availability and latency.
• Failure modes: partial failure, network partitions, split brain, clock skew, and how these show up in real systems.
• Idempotency, retries, backpressure, timeouts, circuit breakers, and rate limiting as first-class design concerns.
• Health checking, failure detection, leader election, and graceful degradation.
• Observability: metrics, logs, and tracing as design inputs, not afterthoughts.
• Practical experience with API design (REST or gRPC), relational databases, and asynchronous messaging or event streaming systems, with a clear understanding of transactional and consistency boundaries.
• Comfortable with AI-assisted development tooling, with the judgment to use it to accelerate work while remaining accountable for correctness, security, and design quality
• Track record of production ownership: on-call, incident response, post-mortems, and continuous investment in reliability and performance.
• Strong written and verbal communication skills; ability to write clear design documents and collaborate effectively across time zones.
• Consistency and consensus models (strong, sequential, eventual; Paxos / Raft at a conceptual level).
• Replication, sharding, and partitioning strategies, and their tradeoffs against availability and latency.
• Failure modes: partial failure, network partitions, split brain, clock skew, and how these show up in real systems.
• Idempotency, retries, backpressure, timeouts, circuit breakers, and rate limiting as first-class design concerns.
• Health checking, failure detection, leader election, and graceful degradation.
• Observability: metrics, logs, and tracing as design inputs, not afterthoughts.
• Experience building compliance-driven, security-sensitive, or multi-region systems.
• Familiarity with cryptography basics — envelope encryption, key management, HSMs, or PKI.
• Exposure to edge, CDN, or L4/L7 proxy platforms, or to large-scale globally distributed storage or key-value systems.
• Experience contributing to or driving multi-team, multi-quarter engineering programs with cross-functional dependencies across platform, security, and product teams.