Build and validate an AI Chief of Staff prototype that automatically extracts, sorts, assigns, and follows up on meeting action items using LLMs, RAG, and agentic systems. Requires strong GenAI, NLP, Python backend, and productivity tool integration experience.
120k – 120k/yr
On-site5+ YOEML Engineering
About the role
What you will do
Build the meeting-to-action-item extraction pipeline with accurate project and person routing
Develop the auto-sorting engine that maps action items to the correct project context and assignee
Create the nudge and follow-up generation system that drafts communications without human intervention
Ship a working prototype that a single manager can use daily before any team rollout
Validate whether single-player value (one manager, before team adoption) is sufficient to drive retention
Make key decisions around infrastructure and platform choices, balancing prototyping speed with long-term scalability
Apply GenAI building blocks (prompt engineering, agentic frameworks, evals, and guardrails) to real-world development
Collaborate closely with Andrew Ng and the AI Fund team to bring this idea from concept to working product
What you must bring
Demonstrated experience building applications that incorporate Generative AI
Direct experience with workflow automation systems or productivity tool development
NLP pipeline experience for structured extraction from unstructured text (meeting transcripts, emails, documents)
Integration development across workplace tools (Slack, Asana, Notion, Google Workspace, calendar APIs)
LLM application development with prompt engineering and output quality evaluation
Proficiency with GenAI tools and frameworks: RAG, vector databases, agentic platforms (e.g., LangGraph, CrewAI), LLM evals, and guardrails
Strong back-end skills, particularly with Python, and experience with front-end technologies and modern frameworks
Hands-on experience using AI-assisted coding tools (e.g., Cursor, Claude Code) and understanding of best practices for effective use
Proven track record of architecting, implementing, and deploying scalable AI-powered systems
Ability to write scrappy, disposable code for fast prototyping, and clean code for scalable products
Strong communication skills and ability to work collaboratively across disciplines
Nice to have
Experience with meeting transcription or audio processing pipelines
Prior work on task management, project management, or calendar intelligence tools
Experience gathering user feedback directly and iterating based on insights
Exposure to rapid prototyping methodologies and shipping MVPs
Contributions to open-source GenAI projects or tools
Prior experience as a founding engineer or technical lead at an early-stage company
Knowledge of advanced architecture patterns (microservices, event-driven architectures, datastore design)
Interest or experience in product design and product thinking
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