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 — 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 — 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.
What you'll do;
Design and ship vault strategies: take a strategy from thesis and design doc through implementation, simulation, deployment, and live operation — 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 — 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.
What you bring;
A track record of building quantitative systems that run in production — algorithmic trading, portfolio optimization, market making, or risk systems at a trading firm, asset manager, fintech, or crypto-native company. This is often 2–8 years of experience, but we weight what you've built over years on a résumé.
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 — 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.
Bonus points
Hands-on DeFi experience: lending protocols, ERC-4626 vaults, AMMs, or oracle systems — 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.
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.
Who thrives here;
Wants end-to-end ownership — research, code, deployment, and the pager — not a hand-off between research and engineering.
Comfortable that crypto markets don't close. Strategy owners take on-call seriously, and the occasional market-event night is part of the job; we staff and rotate to keep it sustainable.
Operates well in ambiguity: can take "we should have a strategy for X" and return a scoped design, not a list of questions — and is comfortable in a fast-moving space where priorities and team structure evolve.
Holds a genuine risk view and voices it — including "we shouldn't do this" when the analysis says so.
Pragmatic about shipping: balances rigor against client timelines without cutting corners on safety.
Naturally curious about digital assets and DeFi. Deep crypto experience is not required — curiosity and strong quant fundamentals are.
Benefits & perks;
Remote first — work from anywhere in the US & Canada
Regular in-person company retreats and cross-country "office visit" perk
100% paid medical, dental, and vision premiums for employees
$1,000 WFH stipend
Monthly reimbursement for home internet, phone, and cellular data
Unlimited vacation
100% paid parental leave of 12 weeks
Fertility benefits
Opportunity for incentive compensation
Please note at this time our hiring is reserved for potential employees who are able to work within the contiguous United States and Canada. Should you need alternative accommodations, please note that in your application.
The national pay range for this role is $175,000 – $200,000 base plus additional On Target Earnings potential by level and equity in the company. Our salary ranges are based on paying competitively for a company of our size and industry, and are one part of many compensation, benefits, and other reward opportunities we provide. Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.
