Software Engineer, Backend (Infrastructure & Platform)
Claylabs · New York
About this role
## About Clay AI Clay is unleashing the biggest wave of company creation in history. Our mission is to be the engine companies use to grow to their full potential—predicting the next best action and helping teams take it. We started by aggregating the best data for B2B companies, then built the infrastructure to run personalized campaigns on top of it (emails, ads, landing pages, and workflows that make reps more productive). Now we’re building agents to help grow companies. Clay already supports thousands of customers (including Anthropic, OpenAI, Google, and Visa) and is on track to cross $200M in revenue this quarter. ## The Role As a **Software Engineer on one of our Infrastructure or Platform teams**, you’ll work on the systems every Clay product depends on—how work gets executed and scheduled at scale, how services hold up under concurrency, how data is stored and served with predictable latency, and how shared foundations are built so product teams can extend them (not route around them). This role has real latitude. Platform work at Clay isn’t back-office—whether a product team can ship next quarter often depends on the foundation you help build. ## What You’ll Work On - **Scale, reliability, and performance**: Address DB contention, memory pressure, throughput ceilings, and other bottlenecks. Set performance and reliability targets as we scale. - **Platforms other engineers build on**: Define primitives, contracts, and extension points that let product teams ship on shared infrastructure. - **Execution and orchestration**: Evolve how work is defined, scheduled, retried, and observed across the product. - **Observability**: Instrument runs so customers and engineers can see what happened, where it failed, and why. - **Raise the bar**: Set technical direction other teams inherit and pull engineering standards up through design reviews, code review, and the systems you leave behind. ## What Success Looks Like - Product teams ship on shared infrastructure without needing a platform engineer to hold their hand. - The system stays predictable as load grows **10x**, and cost per unit of work goes down. - Large, complex, long-running jobs are boring: they complete, and when they don’t, the reason is obvious. - You can change core system behavior without breaking products built on top of it. - Scale and reliability decisions are made using measured evidence. ## What You’ll Bring - **8+ years** building and operating production systems at scale. - You can spike hard on at least one of: - **Scale, reliability, and performance** (diagnose and fix DB contention, memory blowups, throughput ceilings under real load) - **Platform and frameworks** (build internal platforms other engineers build products on) - You think about platforms as products: you know your consumers, design for their success, and treat confusing abstractions as bugs. - Comfortable with distributed systems, concurrency, queuing, backpressure, and failure recovery—plus the underlying data models. - Clear writing and communication (design docs and RFCs that make tradeoffs legible). - Familiar with (or able to learn quickly): - **React, TypeScript, Python, Node.js** - **AWS** (Aurora/Postgres, ElastiCache/Redis, ECR, ECS/Fargate, Lambda, OpenSearch) - **Terraform** - **CircleCI, Netlify, Playwright** - **CloudWatch, Datadog, Mezmo** - **ClickHouse, Dagster** ## Nice to Haves - Workflow engines, orchestration systems, or durable execution frameworks. - E
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