Senior/Staff Quantitative Engineer

About Seeds Seeds is a fast-growing early-stage RIA fintech startup on a mission to empower financial advisors to supercharge their business growth while delivering a meaningful investing experience for their clients! At Seeds, our core values are the heartbeat of our Company: Trust is our currency and we champion transparency, active listening, collaboration, and a spirit of polite disruption. We’re dedicated to pursuing excellence in all that we do. Our clients are the heroes in our story, and we strive to make their needs the focal point of our innovative solutions. We are eager to welcome ambitious, energetic, and curious-minded individuals to join our innovative and passionate team where every contribution is appreciated, different perspectives are valued, and every voice matters. As a remote-first company, we pride ourselves on having a strong work ethic while embracing flexibility, a healthy work-life balance, and the freedom to work from anywhere in the U.S. You’ll have the chance to collaborate with a small talented team with extensive experience and knowledge in financial services, technology, and startups. Together, you’ll be at the forefront of wealth tech innovation, committed to reshaping a $6.6+ trillion industry and fostering meaningful connections between individuals and their finances. If you’re eager to make a meaningful impact in the financial advisory industry, we encourage you to apply to join us on our exciting journey! The Role As a Senior or Staff Quantitative Engineer, you’ll build and own the optimizer at the center of the Seeds platform. Its inputs are accounts, parameters, and preferences; its output is orders — every strategy we run passes through it. You’ll take end-to-end accountability for the correctness, precision, and validity of its outputs, and their alignment with financial constraints, business logic, and risk parameters. You’ll report directly to the CTO, work across Investments, Trading, and Product, and build hands-on with AI coding agents like Claude Code. The work sits equally in engineering and investments: knowing why a portfolio result is right matters as much as knowing why the code is. Join us in reimagining the future of wealth management. What You’ll Do Build and own the portfolio optimization engine across thousands of accounts — the objective functions and constraints, the optimization modes and why each is set the way it is, mean-variance and convex optimization, index sampling, and tax-aware personalization (lots, restrictions, harvesting, wash-sale rules) — which the data pipelines, investment models, and trading functionality all depend on. Own outcomes end to end , taking a problem from ambiguity to a shipped, correct, maintainable solution you stand behind in production. Design and automate the regression suite that proves every change is a net benefit — coverage and invariant checks across the full cross-section of accounts, because a change that looks great on one account can quietly wreck a segment of others. Diagnose the failure modes unique to optimization — infeasibility, non-convergence, numerical instability, and data-quality faults. Read the output and know whether it’s right — telling a correct result from a plausible-looking wrong one and saying why, and knowing which constraints are regulatory rather than preference. Work AI-native — using agentic workflows to move faster without trading away quality, owning everything that ships, and helping build our prompt, evaluation, and guardrail infrastructure. Turn investment intent into production systems with Investments, Trading, and Product, explaining quantitative trade-offs to non-technical partners. Raise the technical standard — improving the frameworks, patterns, and architecture other engineers build on, and supporting the team’s growth through code review, pairing, and leading by example. Successful Candidates Will Have Senior-level experience building and shipping production quantitative or numerical software (6+ years) — ideally on a small, fast-moving team. Strong production engineering fundamentals — design patterns, object-oriented and functional programming, and a real sense of what makes code production-grade (we’re mostly a C# shop, but the fundamentals matter more than the language you have them in). Hands-on portfolio-optimization expertise — building objective functions and constraint sets, mean-variance/convex optimization, index sampling, working with factor risk models, and real-world limits like tax, restrictions, and personalization, using a solver stack such as Gurobi, MOSEK, CVXPY, or similar. Hands-on with a commercial optimizer and risk model — Axioma, MSCI Barra, Northfield, or comparable. Numerical correctness and validation rigor — you can speak to how you prove accuracy is preserved. Working knowledge of wealth/asset-management constructs — SMA/UMA, asset location, model-of-models, OMS/EMS — or the ability to ramp quickly. Deep familiarity with large financial datasets — time-series, reference, and fundamental data (Bloomberg, Morningstar, FactSet), and the intuition to tell when the data itself is wrong. Fluency with AI-native development — you build with agents like Claude Code daily, with a point of view on where they help and a high bar for what you ship. Demonstrated ownership and strong engineering judgment — you make sound trade-offs independently and care about the difference between “it works” and “it’s right.” Excellent cross-functional communication — including explaining quantitative trade-offs to non-technical partners. B.S./M.S./Ph.D. in a quantitative field (Mathematics, CS, Engineering, Operations Research) — or equivalent demonstrated experience. Bonus: direct indexing / tax-loss harvesting / wash-sale systems · scaling optimization across many accounts (batch/parallel orchestration, shared-input caching, solver warm-starts) · C#/.NET in production · regulated-context experience (SOC 2). How We Work With AI We build hands-on with AI coding agents like Claude Code , and our expectations are: AI is an enhancement, not a replacement. A strong engineer with AI is the bar; AI does not lower the bar for engineering judgment, numerical rigor, or accountability. You own your output. No “the model wrote it” — you are the accountable owner of everything you ship, held to the same standard as hand-written code. That bar is especially high when the output moves money. We’re building toward agentic development. We want engineers who help create the systems, tooling, and guardrails that let us safely delegate more work to agents over time — and who treat velocity and quality as things to compound, not trade off. Compensation & Benefits Pay will be determined based on experience and other job-related factors permitted by law, and may include incentive compensation. Seeds offers a competitive benefits package, including medical, dental, and vision; an open PTO policy; company-paid holidays; and remote-work flexibility. To Apply Please submit your resume to . For more about the company, visit