Software Engineer, Backend (Infrastructure & Platform)

About Clay

Clay predicts the next best action for your business and then helps you take it. We started by aggregating the best data for B2B companies. Then, we built the infrastructure to run any personalized campaign on top of it, including emails, ads, landing pages, and workflows that make reps more productive. Now, we're building agents that can help grow your company for you. We're already helping thousands of customers — including Anthropic, OpenAI, Google, and Visa — go to market with unique data, signals, and AI research.

In 2026, we raised a $115M Series D at $7.1B Valuation led by Wellington — and are on track to cross $200M in revenue this quarter. We also launched a $1M Scholarship fund for GTME Education.

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 the shared foundations are built so that product teams extend them rather than route around them.

This is a role with real latitude, the Platform work at Clay is not a back-office function. Whether a product team can ship next quarter usually comes down to whether the foundation supports it, and you'll be one of the people deciding what that foundation looks like.

What You'll Work On

• Scale, reliability, and performance. Address DB contention, memory pressure, throughput ceilings, and any other bottlenecks that arise. Set performance and reliability targets that hold as we scale.
• Platforms other engineers build on. Define the 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. Give customers and engineers the instrumentation to see what a run did, where it went wrong, and why.
• Raise the bar around you. 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 rather than up.
• Large, complex, long-running jobs are boring: they complete, and when they don't, the reason is obvious.
• We can change how a core system works without breaking the products built on it.
• Scale and reliability decisions are made against measured evidence.

What You'll Bring

• 8+ years of hands-on experience building and operating production systems at scale.
• You spike hard on at least one of:
• Scale, reliability, and performance — you've diagnosed and fixed DB contention, memory blowups, and throughput ceilings on systems under real load.
• Platform and frameworks — you've built internal-facing platforms that other engineers built products on.
• You think about platforms as products. You know who your consumers are, you design for their success, and you treat a confusing abstraction as a bug.
• You're comfortable reasoning about distributed systems, concurrency, queuing, backpressure, and failure recovery, and about the data models underneath them.
• You write and communicate clearly. Your design docs and RFCs make tradeoffs legible and move alignment forward.
• You're familiar with our current tech stack or can 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

• Experience with workflow engines, orchestration systems, or durable execution frameworks.
• Experience taking a system from internal tool to company-wide platform, including migrating existing consumers onto it.
• Experience with multi-tenant systems.
• Experience running LLM calls or agent loops inside a production execution path.
• Experience with data-intensive systems: search infrastructure, large result sets, or high-volume ingestion.

How We Work

We're a cross-site engineering org split between NYC and SF, working in two-week sprints with async planning in Slack, weekly cross-functional team meetings, and Linear as the source of truth for everything we're building.