Principal Product Engineer

1 мес. назад

220k–280k USD / yearUSALeadRemote

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Develop and engineer the core product platform enabling rules-based investment methodologies and AI-powered investment strategies.

О компании

We're a team of ~25 senior-to-principal engineers, designers and AI/ML researchers. More than half the team are former founders. We move fast, challenge assumptions, and believe AI should fundamentally change how financial products are built. We have no management hierarchy and work remotely with 4 one-week hackathons per year. “Full stack” to us means you own a slice of the product, including its roadmap and go-to-market.

Обязанности

Creating an investable index from a conversation with AI isn't a traditional engineering problem. Users aren't filling out forms or clicking through dashboards—they're collaborating with an intelligent system to express a thesis, understand how it's constructed, and iterate on it over time.
We're looking for a Principal Product Engineer who thrives in ambiguity, enjoys solving complex technical problems, and wants to define what AI-native investing looks like.
You'll work directly with the founders, designers, and AI/ML researchers to shape both the product and the company. This isn't a role where you'll be handed requirements. You'll help identify opportunities, influence technical direction, and set the standard for engineering across .
Own major product areas from architecture through production, shipping features that customers use every day.
Build across the stack—from AI orchestration and backend services to APIs and frontend experiences.
Work closely with designers and AI/ML researchers to turn ambitious product ideas into fast, reliable software.
Design systems that scale while remaining simple enough to evolve as the product changes.
Make thoughtful engineering tradeoffs between speed, quality, and long-term maintainability.
Identify technical bottlenecks before they become organizational bottlenecks.
Raise the engineering bar through technical leadership, code reviews, mentoring, and a bias toward pragmatic execution.
Continuously improve how we build by leveraging AI throughout development, testing, debugging, and deployment.

Требования

You've spent years building products, not just software, and understand the difference.
You naturally think about customer outcomes alongside technical implementation.
You have strong engineering fundamentals and are comfortable working anywhere in the stack when the product requires it.
You're able to decompose messy, ambiguous problems into simple, maintainable systems.
You know when to invest in architecture and when to optimize for shipping.
You communicate technical ideas clearly and enjoy working closely with designers, researchers, and founders.
You're comfortable taking ownership without waiting for direction and enjoy building from first principles.
You believe AI should fundamentally change how software is built and actively use it as part of your engineering workflow.

Условия

Competitive base salary and meaningful equity package
Direct partnership with the founders and a team where more than half are former founders.
Comprehensive health and dental benefits.
A remote-first, flexible work environment.
The opportunity to help define a company creating a new category in capital markets.

Другое

Agora Intelligence is building the audited methodology layer agents call before touching portfolios. Our product, , is GitHub for rules-based investment methodologies: an open platform and marketplace where investment strategies are created, tested, audited, and distributed — by humans and AI agents alike. As AI agents begin managing real portfolios, they need a trusted source of verified investment logic before they can act. is that source.
We operate across two connected surfaces: InvestOS , an open standard that lets any brokerage or platform plug verified methodology into its own AI experience; and , the reference implementation of InvestOS. is an agentic harness where investors, portfolio managers, and creators can author, remix, and publish strategies. We're a small, senior team (from BlackRock, Bloomberg, BGI, and Quant Funds) backed by Portage Ventures, Lerer Hippeau, Cumberland Investments (and more), working with major brokerages and financial data providers.
InvestOS — an open standard for rules-based methodologies and its reference implementation.
We believe any idea — a theme, a trend, a thesis — can be turned into an investable view. On , anyone can express a view as a rules-based basket of assets in seconds, backed by evidence and scored against what actually happens. Whether you're modeling a thematic strategy, tracking an emerging technology, or capturing the public-market footprint of a private company, what used to take an index committee months now takes an API call — 100× faster, at a fraction of the cost. We also transform views found on the open web, into rules-based strategies. This lets us measure the performance of any opinion or prediction about the future. The unit is a : a creator-authored view of the world.
The bigger bet: as AI agents take on more of investing, they'll need an open, trusted standard for how investment views are expressed, verified, and combined. When anyone can generate a strategy in seconds, the strategies aren't the asset. The system that versions, tests, and grades them is. We're building that standard — and the platform where those views are made. We’re also building the learning loops for when views resolve against reality, as measured by markets.
Experience building AI-native products, agentic systems, or developer platforms.
Experience designing and operating production systems with high reliability and observability.
Strong intuition for product—you enjoy shaping what gets built, not just implementing requirements.
Experience at an early-stage startup where you've owned significant technical decisions.
A track record of simplifying complex systems rather than adding unnecessary complexity.
You're energized by difficult technical problems and continuously seek better ways to build software.
A link to your Github, portfolio, or examples of your work.
A short note about a product you've built that you're most proud of, including the problem you solved and your role in the outcome.
A few sentences on why you're interested in .