Founding Engineer (Product)

The problem we're obsessed with

The best analytical work in the world is locked inside human heads and PowerPoint slides. It doesn't compound. It doesn't scale. Every engagement starts from zero.

A market map built this year gets filed away. The judgment a senior consultant develops over a decade — about what questions to ask, where the risks hide, how to structure a narrative — disappears when they move firms. Extraordinary talent. Workflows that haven't changed in twenty years.

Riplo is a software company. We build the operating layer that makes expert analytical work repeatable, scalable, and compounding — starting with private equity diligence, the most rigorous, high-stakes analytical workflow in finance.

We raised $3.1M in pre-seed in December 2025, led by Cherry Ventures, with angels from McKinsey, BCG, QuantumBlack, OpenAI, Goldman Sachs, and Hg Capital.

The category is being defined right now. This role is how we build it.

What you will do

• Define the product DNA. You are not joining a team with a 20-page PRD and a backlog to clear. You are one of the first engineers — which means you make product decisions, own the architecture, and ship things that become the foundation everything else is built on. The choices you make in the next twelve months will be the ones we live with for the next ten years.

• Build beyond the chatbot. We are not building a wrapper around an LLM. We are building multi-step agentic workflows that move past simple RAG into reliable, enterprise-grade inference — and interactive interfaces that practitioners actually want to use. You design the system, not just the pipeline.

• Own the full product surface. From data ingestion to client-ready output, you own the end-to-end stack. Frontend, backend, infra, evals — you make the calls and you ship the result. No handoffs, no committees.

• Translate consulting inefficiency into product. You understand how knowledge work actually gets done — the spreadsheet orchestration, the slide assembly, the fragmented synthesis. You have opinions on how it should work. You turn those opinions into software.

• Everything else that matters. At this stage, the job changes week to week. What stays constant: you are in the room for every critical decision, and you co-own what follows.

The mindset

• Obsessed with impact, not interesting tech. You care about what ships and what customers use — not what looks impressive in a design doc. You default to the highest-impact MVP and you move fast. You measure your own success in customer outcomes.

• Systems thinker. You think in primitives and composition, not features. You identify the fundamental building blocks, design around underlying user needs, and build infrastructure that scales — not tickets that close.

• Owner, not executor. You do not wait for specs. You see what needs to happen and you make it happen. If something is broken and it affects the mission, it is your problem to fix — even if it is not your job.

• AI-native by default. You already build, deploy, and scale end-to-end AI agents. You are a power user of Cursor or Claude Code, constantly exploring new tools, and genuinely excited about how AI changes the way you work — not just what you build.

• High bar, low ego. You hold yourself to a standard higher than what is asked. You seek feedback, close loops, and when someone has a better idea you say so.

Who you are

You are a product-minded full-stack engineer with deep technical experience in TypeScript/NextJS and LLM frameworks — PydanticAI, LangGraph, or equivalent. You have shipped end-to-end AI agents in production, not just prototypes.

You have some exposure to how consulting or professional services firms actually operate — either as a former consultant or as an engineer embedded in those workflows. You understand the problem from the inside.

You have clear evidence of sustained high performance; inside or outside of work. We do not care about pedigree for its own sake. We care about what you have actually built and how fast you learn.

Our stack: Python, TypeScript, Pydantic/LLM frameworks, React/Tailwind, AWS, Terraform, PostgreSQL, Modal.

Why this job, why now

Most engineers who are right for this role are good at their current job. On track. The path ahead is clear. This is not that path.

This is the moment before the category exists; when the architectural decisions you make about how AI-native analytical work should be built will be the ones the industry copies in five years.

You will have real ownership of what gets built. Direct access to a founding team from McKinsey, BCG, DeepMind, and Hg who have lived the problem and are rebuilding it from scratch. No middle management, no pointless meetings — just building something that matters.

If you want to do the best technical work of your career and have it actually matter — this is the role.

What we offer

• Competitive salary and meaningful founding-level equity from day one

• More ownership and architectural influence than engineers with far more senior titles at larger firms