Software Engineer
Renegade · On-site
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Job details
- Work model
- On-site
- Salary
- Not listed by source
Job description
About Renegade We're building the first dark pool built natively for onchain markets. Renegade is an onchain dark pool, a private exchange for institutional crypto trading, fully onchain with no trusted intermediaries. In TradFi, dark pools account for roughly 40% of US equities volume. That entire layer of market structure barely exists in crypto. Renegade brings that infrastructure to DeFi. We match orders at the midpoint of the Binance bid-ask spread, without moving the market, without leaking information, and without leaving the chain. Funds, solvers, and market makers that integrate with Renegade get better price execution, with savings on spreads, market impact, and fees. Since launch on Arbitrum and Base, Renegade has processed $336M in all-time trading volume with $100M in daily order flow. We've been live since late 2024, are well-funded by leading investors. We are a lean high-caliber team that works in person in San Francisco. You can see the work directly here: Docs https://docs.renegade.fi/ Code https://github.com/renegade-fi/renegade About The Role We are seeking a systems-focused engineer to join our close-knit team. In this role, you will have strong ownership of core systems and a wide surface area to make a tangible impact. Example projects: - Design a scalable onchain event ingestion + indexing pipeline - Optimize our hedging stack to improve delta neutrality for altcoins - Debug gnarly distributed-systems issues (e.g. raft / consensus edge cases) - Benchmark + optimize our ZK prover stack to raise throughput / rate limits You can shape the role: if you want more customer-facing work, great. If you want to go heads-down and aggressively optimize performance and reliability, also great. About You You’re excited by hard systems problems: trading infrastructure, ZK, distributed systems, performance-sensitive Rust, etc. You’re also senior-leaning on systems judgment: - You’ve built/operated production systems and can anticipate scaling + failure modes - You have taste: you push for simpler designs, strong invariants, good observability - You are thoughtful: you can design safe systems that manage 7 figures of onchain funds - You can move fast without making the codebase impossible to understand If this fits, we look forward to chatting!
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