Member of Technical Staff

About

About Eragon

Eragon is building an enterprise-grade AI operating system. The thesis is simple: software as we know it is dead. Buttons, menus, and dialog boxes are relics. The future of enterprise runs on prompt-driven, agent-powered tools that companies own, control, and deploy in their own cloud environment. Eragon post-trains open-source models on customer data, integrates with the entire enterprise stack, including email, Slack, ERPs, and CRMs, and lets employees and executives take action via natural language. When a CEO wants to know which deals might slip, they ask Eragon. When someone needs to onboard a customer, spin up a dashboard, or approve an invoice, Eragon handles it. Company data never leaves its own servers, and model weights become valuable corporate assets over time. $12M seed raised, led by Long Journey Ventures, Soma Capital, and Axiom Partners. $5M ARR generated in Q1 alone. 50+ customers deploying both locally and in the cloud. Preemptive Series A interest already incoming. The technical team includes a Berkeley CS PhD and an MIT PhD. Featured in TechCrunch. Josh Sirota, Founder and CEO, is targeting $1B by the end of the year.

About the role

Eragon is looking for Members of Technical Staff who can handle everything from modeling to systems and product, taking ideas from concept to real-world production without a roadmap provided. You will report directly to Josh and work alongside one of the most talented and intense small teams in San Francisco. The work is some of the most challenging and interesting in AI right now. The culture is beyond 996. Josh lives above the office. If that excites you rather than concerns you, keep reading.

What you'll own

• System Development and Deployment: Build, integrate, and deploy AI-powered systems into production environments across enterprise customers

Requirements

Must-have

• Model Development: Fine-tune, evaluate, and work with machine learning 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 and Infrastructure: Work with large-scale datasets and integrate systems with internal tools and APIs across customer stacks
• Cross-Functional Collaboration: Partner with product, research, and design to ship end-to-end features
• Evaluation and Monitoring: Implement evaluation frameworks, observability, and feedback loops for production AI systems
• Education: Bachelor's or Master's in Computer Science, Engineering, or a related field

Nice-to-have

• Technical Skills: Strong proficiency in Python and modern engineering or ML frameworks
• Production Experience: Experience building and deploying systems in production environments
• Systems Knowledge: Familiarity with data pipelines, APIs, and cloud infrastructure on AWS or GCP
• Practical ML Experience: Experience working with machine learning models or data-driven systems
• Startup Mindset: Prior experience in a venture-backed, fast-paced environment, ideally as a founding team member or early employee. Big tech backgrounds typically do not thrive here
• Experience deploying or scaling ML systems in production at a meaningful scale
• Familiarity with LLMs, agents, or workflow automation systems
• Experience with distributed systems or large-scale infrastructure
• Background at a frontier AI lab: Anthropic, OpenAI, DeepMind, or equivalent
• High-growth startup background: Databricks, Stripe, Ramp, or equivalent, with a compelling reason for the AI pivot
• Top school pedigree: MIT, Stanford, Berkeley, CMU, Waterloo, or equivalent
• Has lived and worked in the SF Bay Area or a comparable major startup ecosystem
• Prior founding experience or has built and owned something completely end-to-end

Benefits & perks

• Health Insurance
• 401K
• Free Gym Membership

Interview process

1. 1Application Review
2. 2Initial Screen
3. 3First Round
4. 4Second Round
5. 5Work Trial
6. 6Offer
7. 7Hired