San Francisco, CA · On-site · Full-time
Compensation: $250,000–$450,000 + 0.75%–2% equity

About the Company

An early-stage, venture-backed company building an enterprise-grade AI platform that lets companies query and act on their own data, tools, and workflows through natural language — deployed in the customer's own cloud so their data never leaves their servers. The team is small, technical, and moving fast, with strong early revenue traction and a growing enterprise customer base. Founded 2025 · 1–10 people · Industry: AI Tools.

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. This is a fully on-site, very high-intensity environment for someone who wants end-to-end ownership at the frontier of applied AI.

What you'll be doing

• Build, integrate, and deploy AI-powered systems into production across enterprise customers
• Fine-tune, evaluate, and work with ML models in real-world applications
• Design scalable pipelines for training, inference, and data processing
• Improve latency, throughput, cost efficiency, and reliability of production AI systems
• Work with large-scale datasets and integrate with internal tools and APIs
• Partner with product, research, and design to ship end-to-end features
• Implement evaluation frameworks, observability, and feedback loops

Tech stack: Python; modern engineering / ML frameworks; AWS or GCP; data pipelines & APIs.

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

Why Join

• Direct ownership and a direct line to the founder on a small, senior team
• Strong equity (0.75%–2%) and end-to-end scope from concept to production
• Frontier applied-AI work: post-training open models and shipping agent-powered enterprise tooling
• Early-stage company with strong revenue traction and momentum