The job, in the employer's words
TL;DR
The next wave of stablecoin adoption is payments. We're building a stablecoin clearinghouse to make stablecoins move like money, not a trading asset. Payments don't run on trading, but stablecoins currently do, this is unacceptable for traditional payments companies. We're looking for a Senior Platform Engineer who obsesses over correctness/efficiency and likes to get involved across backend/distributed systems. Help us build the systems that help us build faster with confidence by owning and building internal tools, dev infrastructure, and automation.
About Us
We believe stablecoins are better money and will be the backbone of better payments. We see key structural problems hindering stablecoin adoption, and we're going to fix them – starting with building a clearinghouse. We're a small, scrappy team (~10 people) based in NYC, we've raised $10M from a16z crypto and other excellent partners, and we're going to bring better money to the world.
What You'll Own
Correctness of money movement. The invariants, tests, and failure-mode coverage for our ledger, netting, routing, and payment ordering. This includes a reliability layer for the banks, custodians, exchanges, and issuers we depend on: shared clients, rate-limit budgets, retries that respect idempotency, and failure tests for each provider.
The trust layer for AI-assisted development. We work with coding agents every day, with automated review and automated incident analysis in place. You will extend it: verification of agent-written changes, guardrails on credentials and sandboxes, cost and quality telemetry, and evals that show whether the agents are improving. You will also keep a fast-growing codebase easy to read and trust.
Observability that catches problems first. Alerts the team trusts, service-level targets on the flow of funds, and telemetry around the integration edges we do not control. Our monitors live in the repo as code, and we want more of that thinking.
Load and performance. The load tests, the cadence for running them, and a capacity model we believe. This area is open for you to own outright.
Internal tools. The admin surfaces and automation that make a small team feel much larger. You will have strong opinions here. Bring them.
The path to production. CI/CD, environments, deploys, and rollback, built to be fast, safe, and repeatable.
What We're Looking For
5+ years in platform engineering, developer tooling, infrastructure, or reliability engineering, on systems where mistakes were expensive.
Deep production TypeScript in a codebase large enough that types and module boundaries mattered.
Relational data modeling and migrations under production constraints. Postgres or equivalent. Node.js fluency.
GCP or AWS
You reason about state, ordering, idempotency, failure modes, and consistency, and you name failure modes before anyone asks.
You have built resilience around unreliable third-party APIs: rate limits, retries, idempotency, and dropped callbacks.
You have owned the path from code to production and instrumented it.
A real practice around AI-assisted engineering. You have built around models and kept your judgment about code you did not write.
You build internal tools without being asked, and you know what good looks like.
You treat ambiguity as an opening.
Meaningful pluses
Ledgers or double-entry systems
Payments, trading, or regulated infrastructure
Durable workflow orchestration (Temporal, Cadence, sagas)
Terraform and infrastructure-as-code ownership
Property-based testing, fuzzing, or fault injection
TigerBeetle
Build systems and CI performance work
Load and performance engineering
Security-minded platform work in a SOC 2 environment
Crypto experience. If you spent a career on reconciliation, settlement, and clearing at a bank or payments company, your instincts transfer.
Our Values
Be offended by the status quo. A payment taking 3 days and costing 3% is offensive. Every day that people use legacy financial infrastructure costs humanity time and money. Bring the future forward with righteous indignation.
Be all over it. Operate with extreme urgency and accountability. Know the numbers, meet the right people, answer every email, go the extra mile. Ask yourself: can it be done today?
We sell trust. Trust is easy to lose. Security and integrity are our foundation. Use every interaction and every product as a chance to build trust. This is non-negotiable.
Do the dishes. We are all owners. Put ego aside and get shit done.
Be the glue. Pick each other up and make each other better. Be direct, be helpful, and assume positive intent. Win as a team.
We enjoy the crucible. We are on a mission to change money. It takes a lot of optimism to attack a goal this ambitious. Our opportunity is a privilege and we do not forget that, especially when the journey is hard.
Benefits
We are playing the long game, and we think you should too. That means investing in our people. We offer comprehensive and growing benefits:
Competitive salary and equity
Comprehensive insurance (medical, dental, vision)
Unlimited vacation: take time when you need it
Periodic off-sites
Benefits mentioned
- We are playing the long game, and we think you should too. That means investing in our people. We offer comprehensive and growing benefits:
- Competitive salary and equity
- Comprehensive insurance (medical, dental, vision)
- Unlimited vacation: take time when you need it
- Periodic off-sites
Requirements mentioned
- 5+ years in platform engineering, developer tooling, infrastructure, or reliability engineering, on systems where mistakes were expensive.
- Deep production TypeScript in a codebase large enough that types and module boundaries mattered.
- Relational data modeling and migrations under production constraints. Postgres or equivalent. Node.js fluency.
- GCP or AWS
- You reason about state, ordering, idempotency, failure modes, and consistency, and you name failure modes before anyone asks.
- You have built resilience around unreliable third-party APIs: rate limits, retries, idempotency, and dropped callbacks.
- You have owned the path from code to production and instrumented it.
- A real practice around AI-assisted engineering. You have built around models and kept your judgment about code you did not write.
- You build internal tools without being asked, and you know what good looks like.
- You treat ambiguity as an opening.
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