About the Role
About JST Digital
JST Digital is a global financial services firm focused on cryptocurrencies and digital assets, providing liquidity, market-making and financial solutions to institutional investors and blockchain companies.
Founded by a team of highly experienced traders and risk managers from institutional finance, we deliver sophisticated financial products and services to companies and foundations in the digital ecosystem, as well as to investors looking to improve their return on digital assets.
We run algorithmic trading systems across multiple cryptocurrency exchanges around the clock.
Your Impact
You will join the team responsible for the core trading infrastructure that powers JST's market-making and execution operations. This includes exchange connectivity, order lifecycle management, and the backend systems that keep everything running reliably 24/7 across a growing number of venues.
You won't just be building prototypes or writing code that sits in a backlog. You will be contributing directly to the production systems that handle live orders and real capital. Your work will involve building and maintaining exchange connectors over REST and WebSocket APIs, extending our Order Management System, debugging production incidents under time pressure, and improving the observability and resilience of our infrastructure.
This is a hands-on engineering role where the quality of your debugging matters as much as the quality of your code.
Your Responsibilities
- Build and maintain exchange connectivity across major cryptocurrency venues, handling order submission, fills, cancellations and real time market data ingestion.
- Analyze trading history and resolve production incidents: trace fills, diagnose exchange connectivity issues, write reconciliation scripts, and deliver root cause analyses.
- Create and operate monitoring and alerting tools to ensure issues are caught before they reach the trading desk.
- Manage and tune cloud infrastructure — process orchestration, resource allocation, and log management.
- Write tooling and automation for trade operations, data extraction, and day-to-day platform tasks that keep the team moving.
- Support the trading desk by keeping production systems healthy, diagnosing issues as they arise, and ensuring the platform is always available and performing.
What You'll Bring
- A degree in Computer Science, Electrical Engineering, or equivalent. A higher degree and/or several years of experience is a plus but not required.
- A minimum of 1 year professional coding experience with Python, C++ or similar language.
- Valid experience as a Rust Backend developer.
- Solid understanding of asynchronous and concurrent programming patterns, as well as object-oriented and functional programming paradigms.
- Familiarity with networking fundamentals and experience integrating with third-party APIs.
- Comfortable with Linux, shell scripting, version control, and command-line debugging tools.
- A support-oriented mindset — you take ownership of problems end-to-end, communicate clearly with the people depending on your work, and take pride in keeping systems running.
- An evidence-driven debugging approach — you read logs, form hypotheses, and narrow down problems methodically.
- Comfort working in a fast-paced environment where production issues require quick, careful response.
- Experience with cloud infrastructure, time-series databases, in-memory data stores, or process management tools is a plus.
Bonus Points
No prior finance or crypto experience is required.
Requirements
Rust Backend Development
Valid experience as a Rust Backend developer is essential.
Coding Experience
A minimum of 1 year professional coding experience with Python, C++ or similar language is required.
Asynchronous Programming
Solid understanding of asynchronous and concurrent programming patterns is necessary.
Networking Fundamentals
Familiarity with networking fundamentals and experience integrating with third-party APIs is important.
Nice to Have
Experience with cloud infrastructure and process management tools is a plus.
Familiarity with time-series databases or in-memory data stores is beneficial.