---
title: 'Data Product Engineer at Effective AI'
canonical: 'https://feeny.ai/job/data-product-engineer-effective-ai-san-francisco-bx4tadvwwq45'
type: 'job'
last_seen: '2026-09-16'
---

# Data Product Engineer at Effective AI

- **Company:** Effective AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-06-30
- **Last confirmed live:** 2026-09-16
- **Apply:** https://jobs.ashbyhq.com/effective-ai/a0f4ebef-9f71-4886-abc0-4ac5efae0134

## Job description

Data Product Engineer

## About Us

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.

## What You'll Do

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.

Recent work that our team has shipped:

- Real-time search over tens of millions of insurance documents and tens of terabytes of data.
- [Verification-first AI systems](https://effectiveailabs.com/blog/insurance-ai-verification) with source-level audit trails for regulated insurance work.
- A production [multi-agent runtime](https://effectiveailabs.com/blog/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.

## Who You Are

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.

## Role Details

- 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.

Benefits:

- Flexible PTO
- Highly competitive salary & meaningful equity
- Best-in-class medical, dental & vision insurance
- 401k with up to a 4% company match
- $1,200 annual learning and development stipend
- Catered lunches
- Commuter benefits for Bay Area employees
- Home office stipend for remote employees
- Mentorship from experienced founders and access to an elite investor network
- Team building events & happy hours
- Company Offsites
- Backing from top VCs (Lightspeed, Valor)

— 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.

## About Effective AI

## Company Overview
- **One-liner**: Effective AI builds an AI agent platform that serves as the operating system for insurance teams, enabling faster product launches, market intelligence, and governed workflows.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025
- **Founders**: Abhay Mitra (Co-founder & CEO), Arijit Banerjee (Co-founder), Kunal Singhal (Co-founder & CTO)

## Core Business
- **Primary industry**: Insurance technology (InsurTech), enterprise AI
- **Target customers**: B2B Enterprise – insurance carriers (actuarial, underwriting, product, claims, operations teams)
- **Mission / purpose statement**: “The operating system for insurance” – bringing code-first autonomy to a $6 trillion industry still running on PDFs and spreadsheets.

## Products & Services
- **AI Teammate Platform**: A multi-agent system that handles complex knowledge work across insurance workflows. Includes modules for competitive intelligence, product execution (state-ready filings, rules, manuals), underwriting guidance, actuarial analysis, and governance controls.
- **Competitive Intelligence Module**: Real-time monitoring of competitor rate changes, loss trends, and rate adequacy dashboards.
- **Enterprise Integrations & Security**: SOC 2 Type II, SSO/SAML, RBAC, audit logs, SIEM export, private connectivity, configurable data retention – carrier-ready integrations with filing, policy admin, rating, and document systems.

## Market Standing
- **Valuation / Funding**: Raised **$10 million in seed funding** from Lightspeed Venture Partners and Valor Equity Partners (as of early 2026).
- **Key Metric**: Total funding $10 M (private; revenue not publicly disclosed).
- **Notable Investors / Partners**: Lightspeed Ventures, Valor Equity Partners.
- **Growth Signals**: Team of ~16 employees (LinkedIn), with active hiring for founding engineers and enterprise sales. Claims “fastest-growing insurers” as customers. Launched in 2025 and already has a live platform with case studies and blog posts discussing multi-agent runtime and verification-first AI.

## Competitive Advantages
- **Vertical‑first approach**: Designed specifically for the P&C insurance industry, solving workflow problems (PDFs, spreadsheets) with domain‑adapted AI.
- **Enterprise‑grade security**: SOC 2 Type II, private connectivity, no model training on customer data – critical for regulated carriers.
- **Multi‑agent coordination & long‑context reasoning**: Patented techniques (formal verification, RL agent loops) that handle the complexity of insurance rate filings and underwriting decisions.
- **Founding team with insurance operator experience**: Built by former insurance professionals (implied by “built by insurance operators”).

## Strategic Focus
- **Product expansion**: Deepen agent capabilities for actuarial, underwriting, and product teams; broaden to claims and operations.
- **Go‑to‑market**: Scale enterprise sales (hiring Account Executive) and build reference customers among top insurers.
- **Talent acquisition**: Hire founding ML engineers to solve frontier challenges in agentic AI, tool use, and reliable reasoning for insurance.

## Why Work Here
- **Culture**: Small, high‑impact founding team; in‑person collaboration 5 days a week in San Francisco (SoMa).
- **Benefits**: Highly competitive salary + equity, flexible PTO, catered lunches, best‑in‑class medical/dental/vision, 401k with up to 4% match, monthly team events.
- **Engineering focus**: Work on cutting‑edge agentic AI (reinforcement learning, multi‑agent coordination, long‑horizon reasoning) with mentorship from experienced founders and access to elite VC network.
- **Growth**: As an early employee, you’ll have massive ownership and shape product, culture, and technical direction.

## Sources
1. [effectiveailabs.com](https://effectiveailabs.com/) – Product overview, integrations, security, customer claims
2. [linkedin.com/company/effective-ai-labs](https://www.linkedin.com/company/effective-ai-labs) – Employee count, founders, headquarters, industry, funding
3. [jobs.ashbyhq.com/effective-ai](https://jobs.ashbyhq.com/effective-ai) – Job listings, benefits, company description
4. [pingojo.com](https://www.pingojo.com/company/httpseffectiveailabscom/) – Founding ML Engineer job details (salary range, benefits, work model)
5. [effectiveailabs.com/blog](https://effectiveailabs.com/blog) – Blog posts on multi-agent runtime and verification-first AI

## Other roles at Effective AI

- [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-effective-ai-san-francisco-zvx8k94zet8r) — San Francisco, CA