Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE/1DTE BotYenom Capital • bhopal, India
Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE / 1DTE Bot
Yenom Capital • bhopal, India
7 days ago
Job descriptionTrades ES futures and options overnight / pre‑market (approx. 6 : 00 PM–9 : 30 AM EST ) Trades SPX 0DTE and 1DTE options during regular hours Uses multiple LLMs , where : One LLM proposes strategies, entries, exits, and risk parameters One or more LLMs critique and challenge those strategies before execution Incorporates Technical Analysis, sentiment, volatility, macro events, and cross‑asset flows Executes multiple staggered entries and exits to improve average prices Analyzes 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 settles Trades via TastyTrade APIs , strictly following defined risk parameters Design 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 risks Implement workflows : proposal → critique → refinement → final decision , with deterministic risk rules as guardrails. 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 levels Use that analysis to : Take ES trades between 6 PM and 9 : 30 AM EST Decide whether to exit or convert ES positions into SPX 0DTE / 1DTE trades after ~10 AM EST . Implement multiple entries and exits : Scaling into positions at predefined technical / volatility levels Layered profit targets and stop levels to improve average prices Build a risk engine to : Set daily Max Loss and Max Profit as a % of portfolio Stop trading once limits are hit Control max exposure, number of positions, and per‑trade risk Support user-selectable : Bias : Bullish only / Bearish only / Both ways Profiles : Conservative / Moderate / Aggressive (affects size, frequency, and risk per trade). Track 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 sentiment Use these events to : Adjust or pause trading around high-risk windows Feed 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. Integrate with our commercial-grade real-time data feed for : ES, SPX, their options, and key cross‑asset instruments Build a robust execution layer using TastyTrade APIs : Handle order placement, modifications, cancels, fills, and error conditions Manage slippage, partial fills, and retry logic Architect a modular system : Data ingestion → TA & signals → LLM council → risk → execution → UI / monitoring Implement monitoring, logging, and alerting for : Strategy decisions & LLM reasoning (traceability) P&L, risk, exposure, and events Connectivity and system health Strong, practical Technical Analysis skills Comfortable with multi‑timeframe chart analysis, indicators, and price action. 4+ years in quantitative / algo trading or systematic options / futures development Strong programming in Python (or similar, with willingness to build in Python) Hands-on experience with : Automated trading systems using real-time data Options and / or futures trading (SPX / ES strongly preferred) Intraday or short‑dated strategies Solid understanding of : Options greeks, IV, skew, and term structure ES and SPX microstructure, especially around macro events Risk management and drawdown control 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. 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. Direct experience with SPX & ES 0DTE / 1DTE strategies Experience with : Cloud (AWS / GCP / Azure), Docker , and basic DevOps Dashboards (Streamlit, Dash, Grafana, or custom web UI) Background in time-series ML, regime detection, or reinforcement learning Macro or cross‑asset trading experience. Excellent base salary , commensurate with experience Attractive % of quarterly trading profits based on performance Potential for increased profit share as the system scales.
Job Title : Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE / 1DTE Bot
Location : Remote or Onsite (Flexible)
Type : Full-time / Contract-to-Hire
Compensation : Excellent base salary + 10% of quarterly trading profits
Ref : About Us
We 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 data
- Cross‑asset and macro / event awareness
- Automated execution via TastyTrade APIs
We are looking for a hands-on Senior Quant / AI Trading Engineer to design and build this system end‑to‑end.
Role Overview
You will architect and implement a Smart AI trading bot that :
Key Responsibilities
Multi‑LLM Strategy & Critic Engine
Technical Analysis & Signal Generation (Must-Have)
Trade Management, Scaling & Risk
Macro Events, News & Cross‑Asset Context
Data, Execution & System Design
Required Skills & Experience
Must-Haves :
LLM / AI :
APIs & Infrastructure :
Nice-to-Have
Compensation
CTC mentioned is in INR from 25L to 50L + 10% of trading profits paid quarterly.
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