You'll be Agara's internal trader from day one, supplying liquidity and bootstrapping markets with a $500K liquidity budget across our CLOB and AMM infrastructure. You are the reason users see tight spreads when they open the app.

Build probabilistic models and actively market-make across fundamentally different market categories: elections, sports, macro (Fed rates, geopolitics), crypto, and culture. Each requires distinct modeling approaches, data sources, and risk profiles.
Operate and refine proprietary quoting systems. Maintain tight two-sided quotes across hundreds of concurrent markets.
Own risk management end to end. Position sizing, inventory management, parameter tuning on AMM markets, anomaly detection, real-time exposure controls, and cross-market correlation monitoring.
Work directly with engineering to improve execution infra, pricing feeds, data pipelines, and tooling. You should be able to code your own tools (Python minimum, Go/Rust a plus).
Produce post-trade analyses that directly inform platform decisions: fee structures (maker rebates, taker fees by tier), liquidity mining reward calibration, market design choices, and which market categories to prioritize based on actual trading data.
Help design and manage external market maker programs: defining quoting obligations (uptime, spread, depth), rebate structures, API access tiers, and SLAs for professional firms we onboard.

What we're looking for:

You've actually traded. Prop trading, market making at a crypto exchange, HFT desk, or quantitative fund. We need someone who has managed real P&L and real inventory risk.
Strong probabilistic thinking and quantitative modeling. You can build a pricing model for "Will the Philippine Senate pass Bill X by March?" from scratch using whatever data sources exist, even when there's no historical dataset to backtest against.
Comfortable coding production-quality tools. Python is the minimum. If you can write Go or Rust, even better. You'll be writing quoting bots, backtesting pipelines, data scrapers, and monitoring dashboards.
Deep understanding of market microstructure. You know what adverse selection looks like, why inventory risk matters, how fee structures shape order flow, and what happens to spreads as a market approaches expiry.

Agara - Quant/Trader for internal MM desk