Eragon — Member of Technical Staff

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 TechCrunchIndustry: AI ToolsWebsite: eragon.aiOffice: 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. Eragon Application 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. #J-18808-Ljbffr davidjoseph-co