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.

• 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.

• Location: Bay Area preferred (3 days/week in our Mountain View office). We're flexible for exceptional remote candidates on the West Coast.

Interview Process

• Intro call with the Head of Talent, 30m

• Technical Interview 1, 60m:

  • Coding / Algorithms / Data Structures, conducted virtually on Google Meet via CoderPad

• Technical Interview 2, 60m:

  • Quantitative / Portfolio Optimization. Work through a portfolio-construction or trade-generation problem; expect to discuss optimization formulation, constraints, and tradeoffs a portfolio manager would care about

• Technical Interview 3, 60m:

  • Backend / System Design. Design and reason about a production data/service architecture (e.g., how a target-allocation change should flow into order generation)

• Culture Interview with the Chief of Staff, 30m

Note: We require at least one in-person interview before making our offer decision. For remotely located candidates, we may request you to visit the Mountain View HQ to meet the team. Depending on your location, you will meet our team member based in NY/New Jersey.

Interview Integrity Notice

To ensure a fair and accurate assessment, candidates are expected to complete all interview exercises independently, without the use of external assistance or AI tools. Arta may, with your consent, request that you share your full screen during technical portions of the interview to verify your work environment. Interviewers may also, with your consent, ask you to temporarily disable virtual backgrounds or filters to confirm your identity and maintain interview integrity. These steps are voluntary, used only for real-time verification, and do not involve recording, storing, or accessing any information beyond what you choose to display during the session.

What We Offer

• A competitive salary and benefits package, with ample opportunities for growth and advancement

• A vibrant and dynamic work environment where innovation, collaboration, and continuous learning are highly valued

• The opportunity to work with a diverse and talented team of industry experts, passionate about shaping the future of finance

• Robust health insurance offering for you and your family

• High deductible health plan available with health savings account contribution

• Generous parental leave

• Competitive PTO benefits

Arta's Compensation Philosophy

We determine your salary based on factors including your interview performance, job-related skills, experience, and relevant education or training. Our offers are based on salary bands that are updated periodically using market benchmarks and consider geographic location as well (for example, higher cost regions like San Francisco or New York). If you are presented with an offer, we will review the base salary, benefits, number of options, notional option value and strike price. We would like to know if you accept our offer within 7 days.

Please keep in mind that the equity portion of your offer is not included in these numbers and represents a significant part of your total compensation.

IC I: $110,000-$180,000
IC II: $160,000-$230,000
IC III: $180,000-$300,000