Data Product Engineer

Effective AI is building a software factory for complex industries: a system of record for how a business actually works. Most companies have databases, workflow tools, documents, dashboards, and expert operators, but the real model of the business - what things mean, when rules apply, what changes over time, what is company-specific versus industry-standard, and how expert judgment gets applied - lives everywhere and nowhere. Effective turns that operating knowledge into governed systems that humans and agents can trust, extend, and act on.

We are starting with insurance as our first deep domain, bootstrapping from regulations, product specs, filings, manuals, standards, market patterns, existing software behavior, and domain expertise to build reusable industry models. Contextbase is our living model of the domain, and RSL - our Rater Specification Language - shows the pattern: messy insurance logic becomes typed, testable, executable, and inspectable. Customers inherit a governed industry model, specialize it for their products and workflows, and keep that specialization correct as the shared model improves.

We’ve raised $10 million in seed funding from Lightspeed Ventures & Valor Equity Partners.

As a Founding Data Product Engineer, you will be a crucial part of our initial team, playing a pivotal role in designing and building from the ground up the layer through which Effective perceives the outside world.

More specifically, you will go out to where the truth actually lives - new filings, regulations, bureau circulars, external data feeds - and turn it into signals the people and agents running the business can trust and act on.

This is a mix of hard data engineering, agent work, and product sense: you own the path from raw source, to the agents that read and reason over it, to the product surfaces where it finally pays off.

• Real-time search over tens of millions of insurance documents and tens of terabytes of data.

• Verification-first AI systems with source-level audit trails for regulated insurance work.

• A production multi-agent runtime that uses cooperative yielding to achieve cheaper and more reliable workflow runs.

• Upstream performance improvements to git in pursuit of faster code agent boot times.

We're looking for an engineer with the judgment to own foundational systems early, and the range to take them from rough idea to production reality.

• You have 4+ years of experience building and operating data systems in production, with a track record that goes beyond writing pipelines to owning them end to end.

• You have a strong computer science foundation and a track record of shipping systems that were hard for reasons beyond code alone: scale, ambiguity, messy data, product constraints, reliability, or organizational complexity.

• You are comfortable operating without a playbook. You can turn an unclear problem into a crisp model, make the right simplifying assumptions, and build the first version that can evolve and scale incrementally.

• You naturally reach for agents as leverage: for research, extraction, validation, testing, and operational work, while relentlessly optimizing the harness around them: the tools, context, evals, and workflows that make them fast, cheap, and trustworthy.

• You are not afraid to explore ambitious technical directions, but you keep the loop tight: fast experiments, clear learning goals, and enough engineering taste to know when to double down or change course.

• Location: San Francisco, CA

• Work Model: In-office 5 days a week

• Compensation: The annual cash compensation range for this position is $210,000–$270,000 based on level in addition to equity & benefits.

• Highly competitive salary & equity

• Flexible PTO

• Catered lunches

• Best-in-class medical, dental & vision insurance

• 401k with up to a 4% company match

• $1,200 annual learning and development stipend

• Mentorship from experienced founders and access to an elite investor network

• Team building events & happy hours

• Backing from top VCs (Lightspeed, Valor)

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Effective AI is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.