Senior Quant

Job Title: Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE/1DTE BotLocation: Remote or Onsite (Flexible)Type: Full-time / Contract-to-HireCompensation: Excellent base salary + 10% of quarterly trading profitsRef:https://developer.tastytrade.com/getting-started/https://github.com/virattt/ai-hedge-fundhttps://github.com/aicheung/0dte-traderhttps://github.com/AlexWan/OsEnginehttps://github.com/marketcalls/openalgoAbout UsWe are building a next‑generation AI-driven options trading system focused on SPX and ES 0DTE & 1DTE. Our goal is to systematically capture 5x–10x intraday option moves by combining:Deep Technical Analysis (TA)A multi‑LLM “council” architecture (strategy + critic, similar to llm-council)Real-time commercial‑grade dataCross‑asset and macro/event awarenessAutomated execution via TastyTrade APIsWe are looking for a hands-on Senior Quant / AI Trading Engineer to design and build this system end‑to‑end.Role OverviewYou will architect and implement a Smart AI trading bot that:Trades ES futures and options overnight/pre‑market (approx. 6:00 PM–9:30 AM EST)Trades SPX 0DTE and 1DTE options during regular hoursUses multiple LLMs, where:One LLM proposes strategies, entries, exits, and risk parametersOne or more LLMs critique and challenge those strategies before executionIncorporates Technical Analysis, sentiment, volatility, macro events, and cross‑asset flowsExecutes multiple staggered entries and exits to improve average pricesAnalyzes ES from 6 PM EST (prior evening) through 9:30 AM EST, trades ES in that window, then exits or converts ES positions into SPX after ~10:00 AM EST once opening volatility settlesTrades via TastyTrade APIs, strictly following defined risk parametersKey ResponsibilitiesMulti‑LLM Strategy & Critic EngineDesign a multi‑LLM “council” where:A “Strategy LLM” generates trade ideas, entries/exits, size, and risk parameters“Critic LLMs” stress‑test, challenge assumptions, and flag risksImplement workflows: proposal → critique → refinement → final decision, with deterministic risk rules as guardrails.Technical Analysis & Signal Generation (Must-Have)Build TA-based signals using:Multi‑timeframe trend/momentum indicators (EMAs/SMAs, VWAP, MACD, RSI, ADX, etc.)Volatility/range tools (ATR, gaps, opening range, realized vs. implied vol)Market structure (support/resistance, liquidity zones, prior day high/low, overnight levels)Perform detailed ES trend analysis from 6 PM EST (prior evening) to 9:30 AM EST:Direction, strength, volatility, and key levelsUse that analysis to:Take ES trades between 6 PM and 9:30 AM ESTDecide whether to exit or convert ES positions into SPX 0DTE/1DTE trades after ~10 AM EST.Trade Management, Scaling & RiskImplement multiple entries and exits:Scaling into positions at predefined technical/volatility levelsLayered profit targets and stop levels to improve average pricesBuild a risk engine to:Set daily Max Loss and Max Profit as a % of portfolioStop trading once limits are hitControl max exposure, number of positions, and per‑trade riskSupport user-selectable:Bias: Bullish only / Bearish only / Both waysProfiles: Conservative / Moderate / Aggressive (affects size, frequency, and risk per trade).Macro Events, News & Cross‑Asset ContextTrack and integrate major events, including:FOMC, jobs data/NFP, CPI/PPI, GDP, etc.Earnings calendar (especially large index components)Important global geopolitical news impacting risk sentimentUse these events to:Adjust or pause trading around high-risk windowsFeed event context into LLMs for better decision‑making.Monitor cross‑asset markets that drive SPX/ES:Oil, Copper, Gold, Silver, US Dollar (DXY/FX)Detect confirmation/divergence patterns between these assets and ES/SPX, and reflect that in:Trade bias (risk‑on vs risk‑off)Aggressiveness of entries/exits and position sizing.Data, Execution & System DesignIntegrate with our commercial-grade real-time data feed for:ES, SPX, their options, and key cross‑asset instrumentsBuild a robust execution layer using TastyTrade APIs:Handle order placement, modifications, cancels, fills, and error conditionsManage slippage, partial fills, and retry logicArchitect a modular system:Data ingestion → TA & signals → LLM council → risk → execution → UI/monitoringImplement monitoring, logging, and alerting for:Strategy decisions & LLM reasoning (traceability)P&L, risk, exposure, and eventsConnectivity and system healthRequired Skills & ExperienceMust-Haves:Strong, practical Technical Analysis skillsComfortable with multi‑timeframe chart analysis, indicators, and price action.4+ years in quantitative/algo trading or systematic options/futures developmentStrong programming in Python (or similar, with willingness to build in Python)Hands-on experience with:Automated trading systems using real-time dataOptions and/or futures trading (SPX/ES strongly preferred)Intraday or short‑dated strategiesSolid understanding of:Options greeks, IV, skew, and term structureES and SPX microstructure, especially around macro eventsRisk management and drawdown controlLLM / AI:Experience using or integrating LLMs (agents, decision support, tools, etc.)Familiarity with multi-agent / council‑style LLM patterns (proposal vs critic/debate).Ability to design prompts, context pipelines, and guardrails for trading decisions.APIs & Infrastructure:Experience with broker APIs (TastyTrade is a strong plus; IBKR/Tradier/etc. also helpful)Familiarity with real-time data feeds (WebSocket, FIX, vendor SDKs)Strong engineering practices: testing, logging, observability, deployment.Nice-to-HaveDirect experience with SPX & ES 0DTE/1DTE strategiesExperience with:Cloud (AWS/GCP/Azure), Docker, and basic DevOpsDashboards (Streamlit, Dash, Grafana, or custom web UI)Background in time-series ML, regime detection, or reinforcement learningMacro or cross‑asset trading experience.CompensationExcellent base salary, commensurate with experienceAttractive % of quarterly trading profits based on performancePotential for increased profit share as the system scales.CTC mentioned is in INR from 25L to 50L + 10% of trading profits paid quarterly.