Distributed systems engineer - Core infrastructure

About the role

This is a data infrastructure company building the activation layer on top of the modern data warehouse. Hundreds of companies, including Autotrader, Calendly, Cars.com, Monday.com, and PetSmart, use the platform to move customer data from their warehouse into the tools that drive marketing, personalization, and business operations.

Responsibilities

• Sync performance: find and remove bottlenecks across the syncing engine so customers can move large datasets faster and more predictably.
• Distributed execution: design systems that handle scheduling, batching, retries, rate limits, backpressure, and partial failures without hiding complexity behind fragile abstractions.
• Streaming architecture: help evolve the platform from batch-only syncs toward real-time syncs from webhooks, queues, and other streaming sources.
• Scalability and reliability: architect for the next order of magnitude of growth across throughput, latency, infrastructure cost, and operational load.
• Low-latency serving: contribute to infrastructure behind the Personalization API, including caching, query paths, tail latency, and high-QPS production behavior.
• Multi-region and multi-cloud infrastructure: support and extend deployments across regions and cloud providers, including new regions required for customer data residency.
• Customer-scale debugging: work directly with customers to understand their hardest scaling issues and turn those issues into durable platform improvements.
• Technical direction: influence what the team builds, how systems are designed, and where engineering time should be spent.

Requirements

• 7+ years of software engineering experience, with meaningful work on distributed systems, infrastructure, or high-scale backend systems.
• Strong general engineering judgment and the ability to reason clearly about latency, throughput, consistency, retries, failure modes, and operational tradeoffs.
• Experience building systems where correctness and reliability matter under customer load.
• Comfort debugging performance across multiple layers of a system, from application logic to queues, databases, caches, cloud infrastructure, and third-party APIs.
• Experience owning projects from ambiguous problem statement to production rollout.
• The ability to work directly with customers without turning engineering into reactive support.
• Strong communication skills when tradeoffs are subtle and the right answer depends on workload shape, constraints, and failure tolerance.
• A bias toward simple systems that expose the right abstractions rather than complex systems that only work when everything goes right.

Qualifications

• Relevant technical areas: distributed systems, high-scale backend infrastructure, data movement and data pipelines, job scheduling and orchestration, streaming systems, queues, or event-driven architectures, caching and low-latency serving, multi-region or multi-cloud infrastructure, warehouse-adjacent systems, reliability engineering and observability, performance optimization under real production constraints.

Skills

• Good judgment matters more than familiarity with a specific vendor or framework.

Benefits

• Base salary: $180K–$320K
• Equity: competitive
• Location: remote within the US or Canada
• Employment: full-time
• Visa support: available for most visas

Pay

$180K–$320K base + competitive equity

Schedule

Full-time