Senior Backend Engineer (Infrastructure) at Sphere

About the roleMission:Sphere has built the world’s first AI-native tax engine that helps companies like Lovable, Eleven Labs, Replit, Runway AI, Windsurf (+ many more) automate their sales tax, VAT and GST obligations:We're growing rapidly (34%+ MoM revenue growth) and helping the fastest growing tech companies around the world including Lovable, Eleven Labs, Replit, Windsurf, Fathom, Linktree, Photoroom, Sierra AI, Zed etcWe’ve spent the last 1.5 years building local rails into tax authorities in both the US and internationally to properly automate compliance processes (no other vendor has done this)We're building the world's first AI-native tax engine (which will be the foundation for a broader cross border compliance platform; think Deel for international billing)We're well funded by Felicis Ventures and YCAs Sphere scales to support millions of customer transactions globally, the need for scalable infrastructure to support transaction syncing and live tax calculation within checkout and invoices is paramount.Given we are a key part of mission critical billing flows for some of the fastest growing companies in the world, availability, resilience and speed are all key areas of focus that this role would be responsible forWhy this is a massive opportunity:🌍 Massive TAM: Every business around the world needs this. Compliance isn’t optional.🌬️ Strong macro tailwinds: Businesses are expanding globally at a faster pace, while tax authorities are cracking down on cross-border compliance, driving urgent demand.✨ AI advantage: Incumbents can’t scale beyond the U.S.; our AI-native tax engine can.🔮 Product vision: Indirect tax is just the start; we’re building the Deel for international billing.What you will do:Within weeks:Find solutions to Sphere's toughest scaling, performance, and latency problemsWork closely with engineering teamdevelopers to define tooling to help us ship even fasterParticipate in an On Call rotation to solve critical production eventsWork directly with customers like Eleven Labs, Replit, Windsurf, and partners like Stripe, Chargebee, on their latency and availability requirements.Within months:Influence and implement the next generation of Sphere's database, real-time queue, and container orchestration infrastructureWork across our engineering organization to introduce and scale best practices with cloud-native technologies like Amazon ALB, ECS/EKS, Temporal, AWS SQS, Amazon Aurora PostgreSQL, Elasticache Redis, and S3Build abstractions within Terraform to simplify the architecture and increase velocity and ownershipWhat’s important to us:The Dog: Grit > pedigree.Ship fast: If it can be done today, do it today.Self-starter: No hand-holdingAccountability: You’ll be held accountable to objective, measurable targets each month.In-person: SF only.Requirements:Experience managing k8s clusters in AWS/GCP/Azure at scaleExtensive experience shipping high-quality architectures for mission critical systems (focus on high availability, high load, low latency)Experience with Postgres at scaleNice to have:Experience working with large volumes of transaction data. You’ll be getting very familiar with it!Strong experience in Python. Our core application backend and data pipeline services are built with Python and DjangoPassionate about developer experienceVery strong attention to detail. When you work with numbers this is a non-negotiable - it’s not enough to be 99% right.About SphereSphere is an AI-powered cross-border tax compliance platform. We help companies like Lovable, Eleven Labs, Replit and Windsurf automate their sales tax, VAT, GST compliance obligations.What makes us different to other vendors on the market is:we have spent the last 1.5 years building local rails into tax authorities in both the US and internationally to properly automate compliance processes (no other vendor has done this), andwe're building the world's first AI-native tax engine (which will be the foundation for a broader cross border compliance platform; think Deel for international billing).