We're building a system that can make and take decisions inside revenue-critical digital funnels. Not in a sandbox. In production systems where mistakes have real consequences.

The challenge is not generating answers. It is deciding what is true, what matters, and what to do about it under uncertainty. The data is messy, delayed, and often wrong. The same signal can have multiple competing explanations. There is no clean ground truth to train on. Actions can improve or break real business outcomes. Trust has to be earned before the system is allowed to act.

Most AI systems stop at insights because this part is hard. We are building systems that cross that boundary.

Today, our system already runs continuous detection and root cause analysis in production inside mission-critical enterprise workflows. The next step is building systems that can safely take action and improve these funnels over time. If we get this right, software does not just assist decision-making. It becomes part of the decision loop itself.

About The Role

This is a founding engineer role for someone who wants to build real systems from first principles and ship them into production. You will work directly with the founders to design, build, evaluate, and operate the core system. That includes everything from agent behavior and retrieval patterns to backend services, product surfaces, observability, and production reliability.

This is not about stitching together demos. It is about building systems that can reason over messy context, make good decisions, explain themselves, recover from failure, and improve over time. There is no separation here between product, engineering, and company building. You will help shape all three.

What you'll do

Build and ship agentic systems that reason across fragmented enterprise data and workflows
Design retrieval, memory, and context systems that help the product make better decisions over time
Build the infrastructure around the model: orchestration, safeguards, fallbacks, logging, replayability, and monitoring
Develop evaluation loops that measure quality, regressions, trust, and real-world performance
Turn inconsistent signals, business logic, and historical outcomes into durable system context
Design systems that know when to act, when to ask, when to wait, and when to do nothing
Improve reliability under real production constraints like latency, cost, partial failures, and changing data
Work across the stack when needed, including backend systems, product surfaces, internal tools, and data flows
Partner closely with the founders on product direction, technical architecture, and engineering culture

You might be a fit if you

Have built and shipped systems that real users relied on in production
Are comfortable moving across backend, data, and AI application layers
Care deeply about correctness, edge cases, failure modes, and decision quality
Like ambiguous problems where the right abstraction is not obvious at the start
Move fast while keeping quality high
Want real ownership in a small, intense, high-trust team
Have strong product instincts and like building things people actually use

You will probably not enjoy this role if you

You want a narrowly scoped role with clean boundaries
You need complete specs before you can start
You mainly want to do research rather than ship product
You are excited by demos more than reliability
You prefer polished environments over messy, early-stage ones
You optimize for local elegance over end-to-end outcomes

Why this role is special

You will be one of the first engineers helping define the company and the product
You will work on problems where the answers do not exist yet
You will build systems that matter inside revenue-critical enterprise workflows
You will have real ownership across product, architecture, and execution
You will be working directly with an experienced founding team
You will help shape how autonomous decision systems are actually built in practice

Jobs

Founding Engineer (Applied AI)