Founding Engineer

Effective AI•San Francisco, CA

9h•Onsite

About The Position

At Effective AI, we're building the future of work. We believe the real frontier for AI is not simple, repetitive tasks, but complex knowledge work that demands expertise and multi-step reasoning. That's why we're building sophisticated AI Teammates designed to master complex workflows and collaborate with human experts. We're starting by tackling the trillion-dollar U.S. Property & Casualty insurance market, a space with intricate processes and a rich data environment perfect for this challenge. We’ve raised $10 million in seed funding from Lightspeed Ventures & Valor Equity Partners. Our dedicated team is based in San Francisco and thrives on in-person collaboration to solve these challenging problems. As a Founding Software Engineer, you will be a crucial part of our initial team, playing a pivotal role in designing and building our core product from the ground up. You will tackle some of the most significant challenges in agentic AI to develop Teammates capable of handling core insurance functions like underwriting and claims processing.

Requirements

We're looking for an ambitious and creative builder who is excited to tackle hard problems.
You have a strong foundation in computer science and exceptional problem-solving skills, demonstrated through high-impact projects or prior work.
You are genuinely passionate about AI and energized by tackling ambiguous challenges from first principles.
You possess strong coding skills in at least one modern language (e.g., Python, TypeScript, Go).
You are a collaborative, fast learner who wants to join a small team and have an outsized impact.

Nice To Haves

Experience shipping software or familiarity with deep learning frameworks is a significant plus.

Responsibilities

Enable long-horizon task completion by building the foundational infrastructure for AI agents to plan and reliably execute multi-step processes over extended interactions.
Implement nuanced reasoning capabilities , enabling agents to make sound judgments on ambiguous or incomplete data, similar to a human expert.
Build intelligent, tool-using agents that can select and use a diverse set of external tools—including APIs, databases, web searches, and even Excel-based pricing algorithms—to gather facts and take action.
Design systems for continuous adaptation and learning , allowing our AI Teammates to learn from feedback and adapt to dynamic conditions like changing regulations or market shifts.