Quantitative Developer, Liquidity

As a Quantitative Developer for Liquidity at Relay, you will own the analysis, modeling, validation, monitoring, and recommendations that make liquidity decisions rigorous and executable across a cross-chain payments protocol serving over 5 million users. Reporting to the Head of Liquidity, you join a newly formed team defining its operating model while ensuring liquidity remains reliable, competitively priced, capital-efficient, and within risk framework across assets, chains, wallets, CEXs, bridges, and in-flight rebalances. This is a high-ownership, production-facing role where you take ambiguous quantitative problems through analysis, implementation, monitoring, and live operation, with direct impact on pricing competitiveness, execution quality, P&L, capital efficiency, and risk. You will work agentic-first: AI agents accelerate research, analysis, coding, testing, and monitoring, while you remain accountable for methodology, risk, and production decisions.

What you'll do

• Develop portfolio-management and inventory-allocation models across assets, chains, venues, and liquidity systems, including target positions, delta-hedging policies, exposure limits, and stress responses
• Model capital requirements and opportunity costs to allocate liquidity where it creates the most value, and connect model decisions to realized positions, P&L, capital usage, and risk outcomes
• Measure execution and rebalance costs across fees, slippage, timing, price impact, and operational failure modes, and optimize route choice across bridges, CEXs, single-hop and multi-hop paths, and alternative liquidity providers
• Develop decision rules for rebalance confidence, route duration, provider enablement, and when not to execute, using live and historical data to improve execution quality, predictability, and capital efficiency
• Develop client-pricing and fee models across routes, assets, chains, transaction sizes, and market conditions, designing fixed-spread, dynamic-fee, and surge-pricing approaches that remain competitive while covering execution, rebalance, capital, and risk costs
• Evaluate pricing for new client requirements and identify low-liquidity routes, exclusions, capacity limits, and required safeguards; define quantitative inputs for haircuts, seed limits, asset and chain onboarding, and new liquidity mechanisms
• Backtest and validate strategies using realistic costs, out-of-sample testing, scenario analysis, stress testing, and clearly stated assumptions
• Ship model logic with tests, versioned configuration, observability, dry-run evaluation, rollout controls, and human override paths
• Define the position, flow, execution-lifecycle, P&L, cost, and risk telemetry required to compare decisions with realized outcomes
• Investigate live pricing anomalies, high price impact, unexpected P&L, balance drift, and model failures; support incidents, rebalances, and approved operational changes when needed
• Participate in the follow-the-sun on-call rotation, owning quantitative investigation and decision support during your coverage hours and occasionally extending coverage when required

What you bring

• 3-5+ years in quantitative development, quantitative research, trading, market making, portfolio management, risk, or equivalent applied quantitative work
• Strong Python and SQL skills, with the engineering judgment to turn analysis and models into tested, maintainable production systems
• Strong understanding of capital markets and market microstructure, including liquidity, order books, execution costs, slippage, hedging, and risk frameworks
• Experience evaluating models with realistic costs, incomplete data, changing regimes, and out-of-sample evidence
• Track record translating ambiguous business or operational questions into measurable objectives, constraints, assumptions, and decision rules
• Ability to communicate model behavior, uncertainty, risk, and recommendations clearly and operate autonomously within a defined risk framework
• Comfort using AI agents to accelerate research and development while independently validating their output
• A quantitative generalist mindset who enjoys moving between portfolio, hedging, execution, pricing, and risk problems
• Rigor about assumptions, data quality, uncertainty, and out-of-sample evidence
• High ownership from open-ended analysis through production code, live operation, measurement, and iteration
• Willingness to switch from planned research to incident analysis or hands-on liquidity operations when the system needs it
• Strong communication skills across engineering, operations, product, commercial, finance, and leadership partners

Nice to have

• Crypto or blockchain industry experience, particularly with AMMs, bridges, CEXs, stablecoins, and cross-chain liquidity
• Prior work in electronic trading, execution algorithms, market making, portfolio optimization, treasury, or prime brokerage
• Experience building production pricing, risk, hedging, or trading systems with real-money consequences
• Familiarity with simulation infrastructure, model monitoring, P&L attribution, experiment design, and production observability
• TypeScript experience or a track record working closely with backend engineers to integrate quantitative logic into production services
• Experience participating in production monitoring, incident response, and hands-on liquidity or trading operations

What we offer

• Competitive base salary
• Equity package
• Comprehensive health benefits
• Unlimited PTO policy with encouraged minimum
• Remote-first culture with emphasis on collaboration, communication, and flexibility

About Relay

Relay is a cross-chain payments protocol providing instant, low-cost cross-chain bridging, swaps, and transactions. With over 5 million users completing 59+ million transactions and $6+ billion in volume across 85+ chains, Relay is building core infrastructure to abstract chains from end user payments and enable the next billion users to experience blockchain benefits without UX burdens.