Eragon

Working at Eragon

Since , Eragon has built Agentic AI operating system that replaces your entire software stack with a prompt. The team is now people. For a AI company this size, the reality is opportunity to shape your role based on the company stage.

The majority of roles are in San Francisco.

Why applying the normal way doesn't work

Eragon runs an applicant tracking system, but hiring managers still work referrals first. A cold application to Eragon isn't dead, it's just fourth in line behind internal referrals, sourced candidates and recruiter pipelines.

Who to contact at Eragon

What to show them

Eragon post-trains open-source models (Qwen, Kimi) on customer-specific datasets and deploys them in isolated cloud environments. That's not a wrapper, it's a fine-tuning and deployment pipeline that needs to scale across multiple enterprise customers simultaneously, each with different data, different security requirements, and different model behaviour needs. This is the core technical work of the product. Core skills: Python, PyTorch or JAX, LLM fine-tuning (LoRA, QLoRA, full fine-tuning), model evaluation, distributed training, cloud deployment (AWS/GCP/Azure), enterprise data pipelines, model serving infrastructure. Proof of work: Fine-tune a small open-source model (Qwen-7B or equivalent) on a publicly available enterprise dataset, customer support logs, financial documents, or sales data, and write a 2-page technical memo documenting: what you did, what improved, what didn't, and how you'd adapt this pipeline for multi-tenant enterprise deployment where each customer's data must stay isolated. Send the GitHub repo and the memo together.

A cold email that works at Eragon

What Eragon screens for

The TechCrunch article published yesterday described Eragon's team as Sirota plus two technical co-founders: Rishabh Tiwari (Berkeley CS PhD candidate) and Vin Agarwal (MIT PhD). That's three people with $12M in the bank, live enterprise customers, and four open roles that nobody knows about yet because the announcement dropped this morning. The careers page was updated four days before the funding announcement, meaning they opened these roles quietly before going public, and the listings haven't propagated anywhere yet. Axiom Partners explicitly described Eragon as "the connective tissue for how modern teams operate and make decisions", that language maps directly to integration work, data pipelines, and enterprise sales infrastructure hires. Mike Knoop co-founded Make (formerly Integromat), the workflow automation platform that competes with Zapier, his investment signals conviction that Eragon can own the enterprise orchestration layer, and his portfolio experience pushes these companies toward deep integration work. Arielle Zuckerberg at Long Journey Ventures backs founders with enterprise GTM experience and pushes hard on customer success and expansion infrastructure. Soma Capital's portfolio companies at this stage typically need product and design talent urgently. The four roles on the careers page, ML Engineer, AI PM, AI UI/UX Designer, Applied Research Engineer, cover the full stack of what a 3-person technical team with live enterprise deployments urgently needs.

A tailored CV beats a generic one. Use Eragon's job description language to clear filters.

Mistakes that kill Eragon applications

Eragon take-home assignment

Eragon includes a take-home exercise in their interview process. For AI roles, this typically involves a practical problem that takes 2-4 hours. Focus on clean, working code over premature optimization. They're evaluating how you think and communicate, not just the solution.

Eragon interview timeline

Expect days total. Compared to similar AI companies (14 days median), Eragon is about average.

Interviewed at Eragon?

Tell us how it went — stages, questions, timeline. Takes 90 seconds and it's how this page stays accurate for the next person.

Eragon jobs, frequently asked questions