Software Engineer, Infrastructure

Pylon•San Francisco, CA

20h•$180,000 - $250,000•Onsite

About The Position

At Pylon, we're building the future of B2B Post Sales. We’re building the all-in-one B2B post-sales support platform powered by conversational data and layered with intelligence to help our customers run their operations in real-time. We’re backed by a16z, BCV, General Catalyst, Y Combinator. Currently more than 1500 companies including Linear, Cognition (makers of Devin), Modal Labs, and Incident.io run their support and customer success workflows with Pylon. You'll also find us on the Enterprise Tech 30 List. Our product has a very large problem space so there’s a ton of stuff to build and take ownership of - we’d be excited to get your help as we're hiring several extremely talented software engineers across the stack.

Requirements

3+ years in backend or infrastructure engineering and strong hands-on experience with cloud infrastructure.
Highly leverage AI for software development and can juggle multiple workstreams at the same time.
Have worked at startups previously and navigated ambiguous environments.
Genuinely enjoy building scalable and reliable systems
Have a growth mindset, want to constantly improve, and want to receive feedback.
Are in SF or you're willing to relocate, you love working in-person, and you're serious about joining us to build a culture we'll all love

Nice To Haves

Experience with our tech stack (React, Golang, GraphQL, and AWS).
Experience with building agentic products in production.

Responsibilities

Design and maintain the core infrastructure across our cloud environments — own it end to end, not just keep the lights on.
Prevent incidents before they happen. Build the monitoring, alerting, and observability that catches problems while they're still small.
Make our systems scale. Find the limits before our growth does and engineer past them.
Own developer velocity. Build the CI/CD pipelines and internal tooling that let every engineer here ship faster.
Hunt down performance bottlenecks and speed them up.
Build for an AI-first workflow — lean on agents and automation to do more with a small team.