Software Engineer, Backend (Infrastructure & Platform)

Clay Labs•New York, NY

1d•$170,000 - $300,000

About The Position

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.

Requirements

You have a proven track record of execution, with 8+ years of hands-on engineering experience building and operating production systems at scale.
You spike hard on at least one of: Scale, reliability, and performance, where you've fixed DB contention, memory blowups, and throughput ceilings on systems under real load; or Platform and frameworks, where you've built internal-facing platforms that engineers across a company 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 love being a product manager as well as an engineer. Our engineers drive and own their areas end to end, including the judgment calls about what's worth building.
You are an empathetic communicator. You express nuanced ideas clearly at different levels of abstraction for different audiences. In disagreements, you prioritize curiosity over confrontation, making sure everyone feels heard and understood.
You love to collaborate with others to ship high quality, thoughtful features. You care about craft and translate the solution into bug free, easily understandable code and raise the engineering bar for those around you.
Having a diversity of perspectives is important to you. You believe that having people with different backgrounds and perspectives creates a better team and a more holistic product.
You're comfortable reasoning about distributed systems, concurrency, queuing, backpressure, and failure recovery, and about the data models underneath them.
You're familiar with our current tech stack or can learn unfamiliar technologies quickly. Our current tech stack is: React, Typescript, Python, Node.js, AWS services: Aurora (Postgres), Elasticache (Redis), Elastic Container Registry (ECR), ECS (Fargate), Lambda, OpenSearch, IaC: Terraform, Deployment tools: CircleCI, Netlify, Playwright, Observability tools: Cloudwatch, Datadoc, Mezmo.

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 where one customer's workload can't degrade another's.
Experience running LLM calls or agent loops inside a production execution path, where cost and latency both matter.
Experience with data-intensive systems: search infrastructure, large result sets, or high-volume ingestion.

Responsibilities

Scale, reliability, and performance. Attack DB contention, memory pressure, throughput ceilings, and the bottlenecks that surface as concurrency climbs. Set performance and reliability targets that hold as load grows an order of magnitude.
Build platforms other engineers build on. Define the primitives, contracts, and extension points that let product teams ship on shared infrastructure instead of forking it. Then migrate the existing consumers onto it.
Own execution and orchestration. Evolve how work is defined, scheduled, retried, and observed across the product, without breaking what's already running on it.
Make the system legible. Give customers and engineers the instrumentation to see what a run did, where it went wrong, and why, at a scale where nobody can trace it by hand.
Handle the seams. The hardest problems usually live where two systems meet: input mapping between products, integrations, data access, credit and usage accounting. These are foundational to our core UX, not edge cases.
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.