Quantitative Developer

PHNX Securities is building a next-generation quantitative trading firm.The firm operates with a disciplined, research-driven approach: robust backtesting, clean execution infrastructure, strict risk controls, and complete regulatory readiness.

Our philosophy is to develop a deep understanding of financial markets, translate that knowledge into robust models, and deploy systematic strategies across global markets with discipline and precision.

At our core, we THINK, STRATEGIZE, BUILD, and TRADE.

combine research, automation, and disciplined risk management to create scalable, repeatable, high-conviction systematic strategies

We are seeking an experienced HFT Quantitative Developer to design, build, and optimize ultra-low-latency trading infrastructure supporting the research, deployment, and live operation of quantitative trading strategies.

The role sits at the intersection of quantitative research, market microstructure, and high-performance engineering, with a primary focus on production-grade C++ systems and latency-sensitive execution across futures and options markets.

• Productionize quantitative research into high-performance C++ trading systems used for live HFT and market-making strategies across equities, futures and options exchanges.
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• Design and optimize execution logic, including:
• Order placement and cancellation strategies
• Queue-positioning logic
• Microstructure-aware order types
• Latency-critical workflows and tick-level decision paths
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• Develop, optimize, and maintain options trading systems, including execution logic for equity, index, and complex options structures.
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• Implement and maintain market-data adapters, handling L3 / full order-book data at scale with high throughput and minimal latency.
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• Develop visualization dashboards (using Streamlit, Dash) to track live and historical performance.
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• Collaborate with the Quant Research Analyst to define rule sets and improve predictive signals.
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• Continuously refine models with feature engineering, statistical validation, and risk constraints.

• Apply deep understanding of market microstructure, including:
• Queue dynamics and adverse selection
• Tick rules and exchange-specific behavior
• Latency paths and order-book dynamics
• Option auction, expiration and market-impact mechanics
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• Support market-making and HFT strategies in futures and options; experience with volatility trading products is highly valued.
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• Optional/desirable exposure to volatility surface modeling, variance swaps, volatility swaps, and cross-asset HFT monetization.

• Build and enhance microstructure-accurate backtesting and simulation engines for execution and strategy validation.
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• Develop historical simulation frameworks to evaluate latency effects, queue positioning, and execution quality.
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• Collaborate closely with quant researchers to:
• Understand signals, assumptions, and expected behaviors
• Translate prototypes into robust, production-ready systems
• Lead research initiatives through the full software development lifecycle

• Engineer cloud-based data and services infrastructure to support large-scale research and trading workflows.
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• Build and maintain robust data pipelines and databases that ingest, normalize, and validate large volumes of market and alternative data.
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• Design and deploy data quality monitoring systems across research and portfolio management platforms.
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• Develop intuitive research APIs and tooling to provide efficient access to data, models, and compute resources.

• Deploy, monitor, and support strategies in live trading environments, diagnosing:
• Latency bottlenecks
• Performance drift
• System instability and failures
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• Implement CI/CD pipelines, DevOps best practices, and automated testing to ensure reliability and rapid iteration.
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• Take ownership of production systems, ensuring ongoing robustness, accuracy, and performance.
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• Provide mentorship to junior developers and promote engineering best practices.

• Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Engineering, Statistics, Financial Engineering, or a related field with 1+ years of relevant experience in HFT .
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• Mandatory HFT experience; market-making experience strongly preferred.
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• Proven experience productionizing HFT or mid-frequency strategies in live trading environments.

• Expert-level modern C++17+, multithreading, low-level optimization.
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• Advanced Python for research, tooling, and infrastructure.
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• Strong Linux/Unix development experience.
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• Experience with object-oriented design, design patterns, and performance-critical systems.
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• Familiarity with testing frameworks, TDD concepts, and code coverage tools.

• Strong foundation in quantitative finance, mathematics, statistics, and econometrics, including:
• Probability and linear regression
• Time-series analysis
• Quantitative risk management
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• Deep understanding of options markets, including:
• Options pricing models
• Delta hedging and risk management
• Equity and index options
• Complex option spreads
• Volatility products (Var Swaps, Vol Swaps)
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• Ability to read and implement mathematical and algorithmic specifications accurately.

• Experience with databases: SQL (Oracle, Snowflake), NoSQL, Graph, and time-series/analytics platforms.
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• Experience with batch and API technologies (Airflow, Autosys, FastAPI, Flask).
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• Cloud experience on AWS / GCP / Azure (Lambda, S3, EC2, EKS).
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• CI/CD experience using Git, Jenkins, and modern DevOps workflows.

• Options trading or volatility trading infrastructure.
• FPGA familiarity.
• Experience supporting intraday or faster trading systems.
• Exposure to machine learning and statistical modeling libraries.
• Experience with large-scale distributed or high-performance computing systems.
• Background in top technology or financial firms.
• GPU/CUDA experience is a plus.