Backend & Distributed Systems Engineer

About SCRYPT

SCRYPT is where money moves: across borders and currencies, on-chain and off. One platform brings together payments, trading, custody and asset management, connecting stablecoin and fiat rails for institutions that move money at scale. Clients are supported by a human desk that runs 24/7.

SCRYPT is a multi-jurisdictional licensed platform headquartered in Switzerland. Licensing and entity information: scrypt.swiss/regulatory.

About the role

We're building the infrastructure and product layer that powers institutional crypto trading, and we're looking for a full stack engineer whose centre of gravity is on the backend. You think in systems - services, data flows, distributed state - and you bring working knowledge of TypeScript and React so you can ship a feature end-to-end when needed, without waiting for a handoff. 

You'll own critical platform services in Java, Go, Rust, or Kotlin - designing the APIs, data models, and integrations other products depend on - in a financial context where an off-by-one error or a missing audit trail has real consequences. 

You'll also help bring AI into both how we build and what we build - treating it as an engineering problem, not a research project. And you take operational ownership of what you ship: monitoring, alerting, and reliability are part of the job. 

The Bar 

Small team, senior bar, AI-native by default. We hire builders who ship, not managers who maintain. One great hire beats three average ones, so we hold the bar even when the seat is empty. Ownership from week one. Velocity from day one. If you need a long runway before you contribute, this isn't the role. 

Key responsibilities

• Design and develop core APIs and platform services in Java, Go, Rust, or Kotlin powering multiple crypto and trading products
• Own PostgreSQL-based data modelling for financial transactions, ensuring correctness, auditability, and migration safety
• Build and maintain integrations with exchanges, wallets, custodians, and compliance systems
• Implement and manage async job processing, message queues, and event-driven workflows across distributed services
• Design and deploy AI-powered features - inference pipelines, LLM integrations, RAG flows, or ML model serving - with production-grade observability and fallback behaviour
• Work with real-time data patterns (WebSockets, event-driven streams) to ensure trading UIs and downstream services reflect accurate, live information
• Instrument, measure, and optimise system performance based on data, not assumptions
• Write ad-hoc queries, read raw logs, and translate findings into clear technical decisions with documented tradeoffs
• Review all code, including AI-generated output, with a critical eye before it reaches production
• Take operational ownership of what you build: deployment, monitoring, alerting, and reliability
• Collaborate with product, compliance, and engineering leads to make opinionated architectural decisions with a multi-year horizon

Requirements

• 4+ years building and owning production backend systems and REST/GraphQL APIs, with strong experience in Java, Go, Rust, or Kotlin (experience in more than one is a plus)
• Strong data modelling and PostgreSQL experience, including complex queries, schema design, and migration strategies
• Solid understanding of distributed systems concepts: consensus, eventual consistency, partitioning, event sourcing, and message-driven architectures - and sound judgement on the tradeoffs (consistency vs availability, event sourcing vs CRUD, when a queue adds accidental complexity)
• Working knowledge of TypeScript and React - enough to build and ship a frontend feature end-to-end when the product needs it
• Hands-on experience building or integrating AI/ML capabilities into production systems: LLM APIs, inference pipelines, retrieval-augmented generation, model serving, or ML observability - with attention to latency budgets, fallback behaviour, and data privacy
• Familiarity with async processing, queues (Kafka, RabbitMQ, SQS, or equivalent), and event-driven patterns
• Experience with financial systems, crypto platforms, or compliance-heavy environments is a strong plus, particularly event sourcing, immutable ledgers, or exchange API integrations
• Enough DevOps knowledge to deploy, monitor, and debug what you build (Docker, CI/CD, cloud basics - we run on AWS)
• Comfortable using AI coding assistants (Copilot, Cursor, etc.) and code review tools effectively - and critically
• Clear written and verbal communication - you can explain a technical decision to a non-technical stakeholder
• Track record in fast-moving teams where shortcuts compound - you can make the case for doing it right without stalling delivery
• Bonus: experience with blockchain data sources and APIs (The Graph, Dune Analytics, etc.)

What we offer

• Real ownership of a function - not a slot in someone else's org chart
• A team where AI tooling is native, not a "transformation initiative"
• Direct access to founders, board, and clients. Flat hierarchy, no middle layers
• Meaningful equity in a Series A institutional crypto company building toward unicorn scale
• Swiss-anchored, globally operating - regulatory rigour where it matters, volume where it counts

Next steps

If you are passionate about building robust platform infrastructure with AI at its core and want to shape the systems behind institutional digital asset trading, we would love to hear from you!