Senior Quant Research Engineer, Trading & Portfolio Optimization

Jobtailor; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Jobtailor seeks a highly capable quant researcher to design portfolio models and production systems in a fast-paced setting. You will work on allocations, tax-efficient trading, and risk management, bringing both research depth and engineering discipline to production-ready solutions.

Responsibilities include backtesting, cross-functional collaboration, and leveraging AI coding tools to accelerate delivery while maintaining high quality and robustness in a startup environment.

Qualifications

• 5 years of experience or strong interest that comes from having worked close to markets or portfolios — as a quant researcher, trader, or in an advisory/PM-facing capacity
• Strong quantitative finance background, with real fluency in portfolio theory, optimization, and risk
• Rigorous math foundation: linear algebra, optimization, probability and statistics
• Strong software engineering skills, with the ability to take a model from research to a reliable, production-quality system
• Comfortable working across the full stack of a quantitative system: data, models, and the services that run them
• Understanding of tax-aware investing concepts such as tax-loss harvesting
• Fluency with AI coding tools and a track record of using them to work faster and at higher quality
• Excellent communication skills — you'll work directly with investment leadership, not just engineering
• Thrives in a fast-paced startup environment, with strong problem-solving skills, high ownership, and comfort working independently amid ambiguity

Responsibilities

• Design, build, and improve the models that determine target portfolio allocations, balancing risk, return, and client-specific constraints.
• Build and maintain the systems that translate those target allocations into real trades, with an emphasis on tax efficiency and cost-aware execution.
• Apply sound risk and portfolio management techniques to keep our strategies robust as markets and client needs evolve.
• Backtest and validate new models and trading logic against historical data before they touch live portfolios.
• Bring an investment/portfolio-management perspective to tradeoffs the team makes, not just a numerical-optimization one.
• Partner with the investment team, product, and engineering to translate investment ideas into shipped, production-quality systems.
• Use AI coding tools as part of your day-to-day workflow to research and build faster.

Skills

Quantitative Finance

Portfolio Theory

Risk Management

Software Engineering

Tax-Aware Investing

Tools

AI Coding Tools

Quantitative Systems

Data Services

Job description

• Design, build, and improve the models that determine target portfolio allocations, balancing risk, return, and client-specific constraints.
• Build and maintain the systems that translate those target allocations into real trades, with an emphasis on tax efficiency (including tax-loss harvesting) and cost-aware execution.
• Apply sound risk and portfolio management techniques — including optimization, factor-based risk modeling, and statistical estimation — to keep our strategies robust as markets and client needs evolve.
• Backtest and validate new models and trading logic against historical data before they touch live portfolios.
• Bring an investment/portfolio-management perspective to tradeoffs the team makes, not just a numerical-optimization one.
• Partner with the investment team, product, and engineering to translate investment ideas into shipped, production-quality systems.
• Use AI coding tools as part of your day-to-day workflow to research and build faster.

Requirements

• 5 years of experience or strong interest that comes from having worked close to markets or portfolios — as a quant researcher, trader, or in an advisory/PM-facing capacity
• Strong quantitative finance background, with real fluency in portfolio theory, optimization, and risk
• Rigorous math foundation: linear algebra, optimization, probability and statistics
• Strong software engineering skills, with the ability to take a model from research to a reliable, production-quality system
• Comfortable working across the full stack of a quantitative system: data, models, and the services that run them
• Understanding of tax-aware investing concepts such as tax-loss harvesting
• Fluency with AI coding tools and a track record of using them to work faster and at higher quality
• Excellent communication skills — you'll work directly with investment leadership, not just engineering
• Thrives in a fast-paced startup environment, with strong problem-solving skills, high ownership, and comfort working independently amid ambiguity

Core Competencies

Demonstrates expertise in quantitative finance, portfolio theory, and risk management, with a strong ability to translate complex models into production-quality systems. Proficient in tax-aware investing concepts and skilled in using AI coding tools to enhance workflow efficiency.

Highest-signal resume keywords

• Quantitative Finance
• Portfolio Theory
• Risk Management
• Software Engineering
• Tax-Aware Investing

ATS Optimization Keywords

Hard Skills

• Optimization
• Linear Algebra
• Probability
• Statistics
• Model Backtesting
• Statistical Estimation
• Risk Modeling
• Data Analysis
• Production-Quality Systems
• Quantitative Research

Soft Skills

• Excellent Communication
• Problem-Solving
• High Ownership
• Independence
• Adaptability

Industry Keywords

• Tax-Loss Harvesting
• Investment Management
• Portfolio Allocations
• Market Analysis
• Client-Specific Constraints

Tools & Technologies

• AI Coding Tools
• Quantitative Systems
• Data Services