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Eragon — Member of Technical Staff

Open 32d

Summary

Build and deploy an enterprise AI operating system that post-trains open-source models on customer data, integrates with tools like Slack and ERPs, and lets employees act via natural language—all while working full-time on-site in San Francisco.

Eragon — Member of Technical Staff

Type: Full-time | On-site | San Francisco, CA Compensation: $250,000–$450,000 + 0.75%–2% equity Hiring count: 1 Visa sponsorship: Yes — H-1B, O-1 Reports to: Josh Sirota, Founder & CEO (no LinkedIn on file)

About Eragon

Eragon is building an enterprise-grade AI operating system. It post-trains open-source models on a customer's own data, integrates across the enterprise stack (email, Slack, ERPs, CRMs), and lets employees and executives take action through natural language — all deployed in the customer's own cloud, so company data never leaves their servers and model weights become corporate assets over time.

Founded: 2025 | Team size: 1–10 (Seed) | Total funding: $12M seed at a $100M valuation (Long Journey Ventures, Soma Capital, Axiom Partners) Traction: $5M ARR in Q1 · 50+ customers (local and cloud deployments) · preemptive Series A interest · featured in TechCrunch Industry: AI Tools Website: eragon.ai Office: San Francisco, CA

Why Candidates Should Join

  • Direct line to the founder: Reports directly to the CEO and works alongside a small, intense SF team.
  • Breakout traction: $5M ARR in Q1, 50+ customers, and preemptive Series A interest at the seed stage.
  • Real ownership and equity: 0.75%–2% equity with end-to-end scope — take ideas from concept to production with no roadmap handed down.
  • Frontier AI work: Post-training open models on customer data and shipping agent-powered enterprise tooling.

Intake Call Summary

  • No intake call transcript was included in the page HTML. An Intake Video is present on the Contrario page but can't be transcribed from the HTML — provide the transcript/notes if you want this section populated.

The Role

Member of Technical Staff who can handle everything from modeling to systems to product, taking ideas from concept to real-world production without a roadmap. Reports directly to the founder/CEO. The culture is described as "beyond 996," fully on-site in SF, and extremely high-intensity (the founder lives above the office).

What You'll Be Doing

  • System development & deployment: Build, integrate, and deploy AI-powered systems into production across enterprise customers
  • Model development: Fine-tune, evaluate, and work with ML models in real-world applications
  • Systems engineering: Design scalable pipelines for training, inference, and data processing
  • Performance optimization: Improve latency, throughput, cost efficiency, and reliability of production AI systems
  • Data & infrastructure: Work with large-scale datasets and integrate with internal tools and APIs across customer stacks
  • Cross-functional collaboration: Partner with product, research, and design to ship end-to-end features
  • Evaluation & monitoring: Implement evaluation frameworks, observability, and feedback loops

Tech stack: Python; modern engineering / ML frameworks; AWS or GCP; data pipelines & APIs. (Derived from Requirements — the page has no dedicated tech-stack section.)

Requirements

  • Bachelor's or Master's in Computer Science, Engineering, or related field
  • Strong proficiency in Python and modern engineering or ML frameworks
  • Experience building and deploying systems in production environments
  • Familiarity with data pipelines, APIs, and cloud infrastructure (AWS, GCP)
  • Experience working with machine learning models or data-driven systems

Green Flags

  • Experience deploying or scaling ML systems in production
  • Familiarity with LLMs, agents, or workflow automation systems
  • Experience with distributed systems or large-scale infrastructure
  • Prior startup experience as a founding team member or co-founder, has operated without structure and thrived
  • High-growth startup background from Databricks, Stripe, Ramp, or equivalent with a compelling reason for pivoting into a heavy AI role
  • Background at a frontier AI lab, Anthropic, OpenAI, DeepMind, or equivalent, signals the technical depth and AI-forward mindset
  • Has lived and worked in the SF Bay Area or a comparable major startup ecosystem and understands the culture
  • Top school pedigree: MIT, Stanford, Berkeley, CMU, Waterloo, or equivalent

Red Flags

  • Only big tech experience with no evidence of startup-speed execution
  • Not AI-forward, views AI as a tool rather than a genuine obsession and area of curiosity
  • Needs a defined scope, a team, or a process to operate effectively, this is a zero-structure environment
  • Not comfortable being on-site full time in SF or not willing to match the intensity of the culture
  • Has not built something meaningfully and owned it in production

Role Details

Salary$250,000–$450,000Equity0.75%–2%Experience2–6 yearsOn-site policyFully on-site, San FranciscoVisa sponsorshipH-1B, O-1Employment typeFull-timeLocationSan Francisco, CA

Required Candidate Q&A (Contrario submission form)

Role-specific questions on the Contrario form beyond the standard Additional Notes field.

  1. Eragon Application
  2. Github or website

No separate call-stage Screening Questions were specified on the page.

Interview Process

Stage 1 — First Round Stage 2 — Second Round Stage 3 — Work Trial Stage 4 — Offer Extended Stage 5 — Candidate Hired — Candidate accepts and starts.

(The page also shows a platform "Pending Approval" stage before First Round; stage descriptions/durations were not provided.)

Ideal Companies & Backgrounds

Ideal backgrounds — OpenAI, Anthropic, Databricks, Stripe, Ramp, Deep Mind Labs Ltd

Note: "Deep Mind Labs Ltd" links to deepmindlabs.ai on the page, which is distinct from Google DeepMind — preserved as listed.

Ideal Candidate Profiles

None provided on the page.

Rejected Candidate Feedback

None yet.

See also

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