Quant Developer

Gauntlet•New York, NY

1d•$175,000 - $200,000•Remote

About The Position

You will design, build, and operate the strategies behind one of the largest asset managers in onchain finance. Gauntlet serves $1.5B+ in client TVL, and the vaults that hold it run on strategies that quant developers on our team build, ship, and stand behind. This is not a research seat where models get handed off to someone else's pipeline â€” you design the strategy, write the code, deploy it, and own it in production. If you want your models allocating real capital onchain within weeks of joining, read on. About Gauntlet Gauntlet builds the financial systems of the future. While much of onchain finance is focused on point solutions, we operate across the entire stack to offer best-in-class vault products. Today we serve over $1.5B in client TVL across some of the largest fintechs/neobanks, protocols, exchanges, and capital allocators in crypto â€” and, increasingly, traditional asset management. Our team brings together traditional finance and crypto-native expertise to deliver durable, sophisticated products for institutional clients moving onchain. The role Depending on your background and interests, you'll join one of our vault strategy teams. Our strategies span lending and credit curation, cross-chain yield aggregation, structured products, RWAs, and more. Teams own the full strategy lifecycle: research and protocol due diligence, strategy design and backtesting, allocation and rebalancing engines, onchain execution and optimization, and 24/7 monitoring of live positions. You own strategies end-to-end and are accountable for their performance, safety, and uptime.

Requirements

A track record of building quantitative systems that run in production â€” algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or crypto-native company. This is often 2â€“8 years of experience, but we weight what you've built over years on a rÃ©sumÃ©.
You write the code behind your strategies. Strong Python and solid software-engineering fundamentals: testing, code review, and the judgment to build durable abstractions rather than one-off scripts. This is a hands-on, quantitative role â€” not a discretionary trading seat.
Applied quantitative skills: optimization, statistics, and simulation, and the instinct to validate models against real data before trusting them.
Comfort with data infrastructure: SQL and experience building or consuming data pipelines.
Production ownership: you've debugged live systems under pressure and understand that a strategy managing other people's money has to be correct, monitored, and recoverable.
Clear technical communication.

Nice To Haves

Hands-on DeFi experience: lending protocols, ERC-4626 vaults, AMMs, or oracle systems â€” as a builder or a sophisticated user.
Solidity / EVM literacy: reading protocol contracts, forked-chain simulation (anvil), or writing adapters; non-EVM experience (e.g., Solana) also valued.
On-chain operational experience: multisig workflows, transaction submission and signing infrastructure, bridging.
TypeScript, and familiarity with a modern data stack (e.g., BigQuery, Dagster, Hex, GCP/Kubernetes).
Experience with risk modeling for volatile or thinly-traded assets: VaR, liquidation modeling, stress testing.

Responsibilities

Design and ship vault strategies: take a strategy from thesis and design doc through implementation, simulation, deployment, and live operation â€” RWAs, leveraged lending, yield aggregation, cross-protocol allocation, perpetuals, prediction markets, and new product types we haven't built yet.
Optimize strategies: signals research, execution optimization, gas-aware rebalancing across tokens and chains, liquidity and duration management.
Run protocol and asset due diligence: evaluate new protocols, collateral assets, and chains for inclusion in strategies â€” solvency mechanics, oracle design, redemption paths, liquidity depth, and more.
Own risk parameters: supply caps, LLTV settings, concentration limits, VaR-based exposure models, and automated de-risking logic that pulls positions when conditions deteriorate.
Integrate new protocols and chains: build and validate adapters for lending markets, DEX aggregators, and bridges; verify strategy behavior against forked-chain simulation before capital touches it.
Monitor what you build: extend our risk-monitoring and alerting systems, define the conditions that page someone, and participate in the on-call rotation for the strategies you own.
Support launches and clients: partner with growth, capital markets, and client teams on new vault and strategy launches.