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)

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

• 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.

• 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.

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).

• →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.)

• 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

• 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

• 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

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

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.

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 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.

None provided on the page.

None yet.