Get hired atEragon×The Anti Job Board

How to Actually Get Hired

Who reads applications, which channel gets a reply, and what they screen for.

50+ peopleSan FranciscoAI

Don't make these mistakes

Avoid: The announcement dropped this morning, which means a wave of generic "congrats on the raise, I'd love to chat about opportunities" messages is already building in Josh's LinkedIn inbox. Stand out by making contact today, before that wave peaks, and leading with something specific and concrete, a proof of work, a specific observation about the product, or a short technical memo. Josh has a GTM background and evaluates people on their ability to think in specifics about customer problems. Generic AI enthusiasm does nothing here. If you are a designer or PM, show you understand the enterprise trust problem in agentic UI. If you are an engineer, show you understand the multi-tenant fine-tuning architecture.

What gets their attention

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.

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

Who decides:the hiring manager
Best channel:LinkedIn or direct email

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

Subject: ML Engineer, [your one-line proof]
Hi Josh, I read the TechCrunch piece this morning. The post-training-per-customer architecture is the right call for enterprise data sovereignty. I fine-tuned Qwen on [specific dataset] last month, hit [X result], and wrote up what the multi-tenant isolation problem looks like from an ML infrastructure angle. Repo and memo attached, worth 15 minutes if the approach resonates?

What Eragon screens for

Screening signal: 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 applications

Generic CVs stand out at a -person company — and not in a good way. Fastest path to rejection.

Skip 'I'm looking for...' — start with Josh Sirota spent years in go-to-market at Oracle and Salesforce implementing enterprise software for large organisations, and his core insight is that the interface itself has become the bottleneck and your specific angle on solving it.

Applying and waiting = silence. Follow up at day five — it roughly doubles your odds of a reply.

Frequently asked questions

How do I apply to Eragon?

Through the roles on our Eragon jobs page, or directly to the hiring manager if you can reach them. At null people, direct outreach outperforms the form.

Does Eragon respond to cold emails?

Response rate data for Eragon not yet confirmed.

Who is the hiring manager at Eragon?

At this size, hiring is usually run by the hiring manager.

How competitive is it to get hired at Eragon?

Expect 100-250 applicants in the first two weeks for AI roles at this size. Apply within 72 hours for best odds.

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