Senior Backend Engineer (Infrastructure)

Every breakthrough in trade infrastructure has followed the same pattern: reduce a transaction cost, expand the market. Containerization for goods. SWIFT for money. Stripe for payments. Compliance is one of the last and largest — and the hardest, because trade rules aren't data to be looked up. They're a complex adaptive system with 190+ sovereign jurisdictions, in different languages, changing constantly, reacting to each other.

Sphere built the system that solves it. Our AI (TRAM) ingests global trade law, interprets it, resolves conflicts across jurisdictions, and produces compliance determinations more reliable than human experts. We handle the entire lifecycle — calculation, registration, filing, remittance — at millisecond latency with zero downtime.

• Backed by a16z and YC. $21M Series A, 30%+ month-over-month growth, customers include ElevenLabs, Replit, Deel, Runway, and Lovable.

• Small team, global surface area. Everyone owns a domain that would be a full team at a larger company. San Francisco, in office.

• The problem keeps compounding.Expanding into input tax, withholding, e-invoicing, tariffs — each multiplies the complexity. Tens of millions of transactions today, billions ahead.

Within weeks:

• Find solutions to Sphere's toughest scaling, performance, and latency problems

• Work closely with engineering team to define tooling to help us ship even faster

• Participate in an On Call rotation to solve critical production events

• Work 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 infrastructure

• Work 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 S3

• Build abstractions within Terraform to simplify the architecture and increase velocity and ownership

• Experience managing k8s clusters in AWS/GCP/Azure at scale

• Extensive experience shipping high-quality architectures for mission critical systems (focus on high availability, high load, low latency)

• Experience with Postgres at scale

• 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 Django

• Passionate about developer experience

• Very strong attention to detail. When you work with numbers this is a non-negotiable - it’s not enough to be 99% right.

You'll thrive here if:

• You're a Dog. You've been underestimated, gone through struggle, and never stopped running. You have a chip on your shoulder and enormous drive. You look at Stripe, Deel, and Flexport all punting on compliance and think: good, that means the opportunity is ours. Hunger beats pedigree.

• Early stage is in your bones. You've built things where there's no playbook and nobody handing you the answer. You define the problem instead of waiting for instructions.

• You own it end to end. Give you a goal and you figure out your own path. Small team, global surface area — everyone owns a domain that would be a full team at a larger company. No one tells you how.

• You believe speed and accuracy are both possible. We're building a complex product that requires robustness and 100% uptime, and we have to build at our customers' pace. Move fast. Don't break things. Both.

• Being in the room is a feature, not a cost. Being in SF isn't a policy, it's how the work gets done. The speed and density of collaboration we need doesn't survive over video.

This won't be a fit if:

• You need structure handed to you or ambiguity feels draining rather than motivating

• You want to manage people more than own hard problems (we're a flat, experienced team — everyone builds)

• You're used to "good enough" shipping (small errors have outsized impact here)