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Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE/1DTE Bot
Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE/1DTE BotYenom Capital • srikakulam, India
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Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE / 1DTE Bot

Senior Quant / AI Trading Engineer – Multi‑LLM SPX & ES 0DTE / 1DTE Bot

Yenom Capital • srikakulam, India
12 hours ago
Job description

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 :

  • Trades 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
  • Key Responsibilities

    Multi‑LLM Strategy & Critic Engine

  • 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.
  • 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 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 .
  • Trade Management, Scaling & Risk

  • 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).
  • Macro Events, News & Cross‑Asset Context

  • 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.
  • Data, Execution & System Design

  • 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
  • Required Skills & Experience

    Must-Haves :

  • 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
  • LLM / 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-Have

  • 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.
  • Compensation

  • Excellent base salary , commensurate with experience
  • Attractive % of quarterly trading profits based on performance
  • Potential for increased profit share as the system scales.
  • CTC mentioned is in INR from 25L to 50L + 10% of trading profits paid quarterly.

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