Why we’re opening this position
Claims handling has been the biggest pain point in insurance for decades. For insurers, the direct and indirect cost runs to 800B every year. For customers, it's the #1 driver of dissatisfaction.
Insurers and brokers alike all agree AI will solve this, but they can't scale it. Nor are the generic AI workflow vendors any match for the messy reality of claims handling. As Warren Buffett put it himself: "insurance always looks easier than it is".
Ellis was founded by insurtech veterans who have built and scaled fully automated AI claims handling. We're now building the leading vertical AI solution for it - designed from the ground up to integrate with systems no API can touch, and to reach human-grade accuracy in weeks instead of years.
Doing this requires building one of the most sophisticated back-office automation products anywhere, where AI autonomy meets the complex reality of insurance claims. It requires redefining what AI engineering can actually do.
Ellis is supported by top tier investors and successful business angels such as the founders of french unicorn Qonto and belgian unicorn Aikido.
The position itself
As a Founding AI Backend Engineer, you own the thing our entire business is built on: a product that does in weeks what the rest of the industry needs quarters - or years - to deliver. Most companies in our space are still fighting to hit human-grade accuracy and reliability at all. We've cracked that. Your job is to make it repeatable, scalable, and fast to deploy - turning a hard technical edge into a durable business advantage.
On the one hand, this means building the engine that powers every deployment:
- Shipping new features to our core AI engine - the models, pipelines, and logic that turn raw client processes into working solutions.
- Designing and building the agents that do the heavy lifting: extracting data, making decisions, taking action, and catching their own mistakes.
- Owning the data layer - ingestion, storage, schema design, and the databases everything else reads and writes to.
- Building the infrastructure an agentic system needs to run reliably in production: orchestration, monitoring, evals, and the tooling to debug when something goes wrong.
Every step of the way, you're:
- Working closely with the business team to translate what clients need into concrete product requirements.
- In the trenches, working side by side with the founders.
- Using AI to speed up your own process - We expect you to harness that power to speed up delivery.
But on the other hand - and more importantly - you're the one making the calls that a senior/staff engineer would make at any other company, on day one:
- Architecture: you're not implementing someone else's design - you're deciding how the system is structured, what gets built vs. bought, and what the stack looks like a year from now.
- Security: as owner of the data layer and infra, you're responsible for how client data is handled, stored, and protected - there's no separate security team to hand this off to.
- Infrastructure & scale: the production, monitoring, and deployment decisions you make now are the difference between a system that scales 10x and one that falls over at 2x.
- Shaping the company vision: to your left and to your right, the business and delivery teams will rely on your technical judgment to set their roadmaps.
Who we’re looking for:
If you're excited by now, it's already a good sign.
When it comes to your competencies:
- Deep technical fluency and genuine engineering craft - you don't just ship code, you understand why it works. This should be evidenced by a master's degree or above in a technical field (CS, Mathematics, or related), or equivalent hands-on experience.
- Experience building complex platforms - systems with real architectural depth, not just CRUD apps or thin wrappers around APIs, including experience building LLM-powered systems based on agent frameworks (LangGraph, ADK, or similar).
- Strong software engineering fundamentals, with deep proficiency in Python and solid grasp of API design (REST/gRPC), Git, and CI/CD.
- Experience with cloud infrastructure and production systems - deploying, monitoring, and debugging services at scale (GCP, Docker, and Terraform are all pluses).
- Bonus points if you've had exposure to the financial services industry, fast-paced start-ups, or if you've founded your own business before.
When it comes to your approach to the job:
- A strong sense of ownership, work ethic, and a low-ego mindset: at Ellis, the best idea always wins, not the loudest voice.
- Excitement for open-ended problems without predetermined solutions. You've got all the support you need, but you're the one who makes the magic happen.
- Comfortable owning ambiguity: fast-moving priorities, evolving requirements, and problems with no textbook answer.
- You take your job seriously but not yourself - what's the point of all this if we're not having fun?
What we offer in exchange
Beyond working on one of the most interesting problems in AI automation, alongside an ambitious founding team, we also offer:
- A competitive salary and benefits package
- Support for your growth - we pay for training, events, etc.
- A flexible remote work policy
How to apply
Send your resume at [email protected]