Senior Quant Research Engineer, Trading & Portfolio Optimization

THE COMPANY Arta is on an audacious and incredibly rewarding mission: to pave the way for people everywhere to lead more successful financial lives. Arta leverages AI and sophisticated digital tools to make financial products once reserved for ultra-high-net-worth individuals accessible to a broader global audience. Think of it as your own digital family office, combining intelligent investment strategies, alternative assets, private market access, and smart automation to help you grow and protect your wealth effortlessly. We value trust, teamwork, and adaptability. THE ROLE Arta manages real client portfolios at scale, and the quality of our investment outcomes depends on a small team that builds the systems behind portfolio construction and trading. We're looking for a senior quant research engineer to help design the models that determine what our portfolios should hold and the logic that executes trades to get there efficiently. This is a hybrid role for someone who thinks like both a quant and an engineer. You'll bring rigorous portfolio theory and optimization skills to bear on real investment decisions, and you'll build and ship the production systems that make those decisions at scale for thousands of client accounts. Reporting to the CIO, you'll work closely with the investment team on what our strategies should optimize for, and with engineering on how they run reliably in production. We're looking for someone who has sat close to markets or portfolio management and brings that judgment to the table, not just someone who has studied portfolio theory in the abstract. WHAT YOU WILL DO - 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. WHO YOU ARE - 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 — giving you intuition for how these systems should behave, not just how to build them.…