Principal AI Engineer collaborating with CEO to build an AI operating system. Work includes designing architectures, building production systems, and shipping impactful features.
Responsibilities
You'll work directly with CEO Vetri Vellore to build our AI operating system from the ground up.
This means you'll touch everything - from designing multi-agent architectures and LLM orchestration, to building production systems, to shipping features that directly impact enterprise customers.
This is a roll up your sleeves and build something from scratch role alongside engineers from IIT, Stanford, and other top-tier institutions who ship production AI daily.
Requirements
7+ years building production software with at least 2+ years deeply focused on LLMs, agents, or AI-native applications
Expert proficiency in Python and experience with React/Next.js for AI-powered UIs
Experience shipping agentic systems to production.
Experience with RAG implementations: Hybrid search, Re-ranking, context optimization, and retrieval quality measurement.
Designed and architected distributed systems at production scale.
Proven ability to influence technical direction across multiple teams while mentoring engineers
Track record of driving ambiguous, high-impact initiatives from concept to measurable business outcomes
Effective collaboration across distributed teams spanning US and India time zones
Bachelor's or Master's degree in Computer Science or related field, or equivalent experience with demonstrable technical excellence
Contributed to open source AI projects or published research
Background in high-scale distributed systems
Based in or willing to relocate to San Francisco Bay Area.
Benefits
Significant equity stake at early stage (15 people = meaningful ownership)
$26M runway, paying enterprise customers, sustainable path—build the right product, not chase next fundraise
Work with founders who've built and sold companies—they know what matters
Day one: You'll be shipping code to production—we deploy daily
First week: Your code will be running in production for enterprise customers
First month: You'll own major features that thousands of users depend on
Six months: Your architecture decisions will define how enterprises operate with AI
Collaborate with engineers from IIT, Stanford, and top-tier institutions who've scaled systems to millions
Take ownership of technical decisions with real autonomy—strong opinions backed by evals get shipped
AI-native culture: use Cursor and Claude Code for development, Claude Code reviews PRs, ship AI features weekly
Flat structure, direct feedback, open technical debates—better ideas win
If you want FAANG stability, this isn't it. If you want to define a category, it is.
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