Software Engineer, Backend (Infrastructure & Platform)
New York City, NY - USA
Department:
Job Summary
Our mission is to help organizations turn any growth idea into reality.
We see growth as a creative practice not a formula. Finding and reaching your best-fit customers takes unique ideas and constant iteration. As AI makes execution faster and tactics easier to copy creativity is the only lasting advantage. Were already helping thousands of customers including Anthropic Notion Google and Ramp go to market with unique data signals and AI research.
In 2025 we raised a $100M Series C backed by world-class investors including Sequoia CapitalG and First Round and crossed $100M in revenue.
In 2026 we announced our second employee tender offer in 9 months at a new $5B valuation. We also launched a community equity round for our customers agency partners and club members.
Some things to know about us:
Our community includes 11000 customers 150 integration partners 125 agencies 50 Clay clubs and 30k members on Slack.
All employees can work for free with world-class coaches who specialize in creativity management and more.
Our operating principles including negative maintenance and non-attached action guide our work. Read more about them here.
Read about us in the NYT Forbes First Round Review and more.
Hear from our employees directly on our Glassdoor page!
As a Software Engineer on one of our Infrastructure or Platform teams youll 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 youll be one of the people deciding what that foundation looks like.
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.
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 dont 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.
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 youve diagnosed and fixed DB contention memory blowups and throughput ceilings on systems under real load.
Platform and frameworks youve 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.
Youre 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.
Youre familiar with our current tech stack or can learn quickly: React TypeScript Python ; AWS (Aurora/Postgres Elasticache/Redis ECR ECS/Fargate Lambda OpenSearch); Terraform; CircleCI Netlify Playwright; CloudWatch Datadog Mezmo; ClickHouse Dagster.
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.
Were 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 were building.
Required Experience:
IC
About Company
Implement your creative growth ideas to build pipeline for your sales team. First, maximize your data coverage with 75+ enrichment tools and our AI agent. Then, use AI to craft the perfect outreach.