Visiting Engineer: STRATA
career, Mountain View, CA, United States
Who we are
AI Fund is Andrew Ng’s venture studio. We identify high-potential applied AI ideas, recruit exceptional builders, and create new companies from scratch. Visiting Engineers join for a 12-week residency in Mountain View to take an idea from concept to working product alongside Andrew and the AI Fund team. If the idea validates, you become a co‑founder. We are backed by a $390M fund from top‑tier global investors. Our purpose is to build AI companies that move humanity forward.
The Idea
STRATA: Regtech copilot that does the work after a new regulation drops.
When a new rule, tariff, or regulatory filing hits, compliance teams don’t just need an alert. They need to understand what changed, figure out the “so what” for their business, and then update a stack of living documents: leadership memos, benchmarking matrices, comparison tables, internal guidance. This work is manual, expensive, and often outsourced to consultants at high cost. Teams in regulated, asset‑heavy industries (utilities, energy, infrastructure) spend 15‑20% of their time on this.
LLMs are excellent at grounded extraction, diffs, and keeping living documents in sync with changing external sources. They struggle at inventing consulting from scratch, but STRATA doesn’t ask them to. The system pulls from trusted primary sources, generates cited redlines and updated cells, routes through a reviewer workflow, and publishes versioned output with an audit trail.
The target vertical is U.S. utilities and energy developers: rate cases, tariffs, interconnection fees.
What you will do
Build the regulatory filing ingestion pipeline that monitors and parses filings from FERC, state PUCs, and relevant regulatory bodies
Develop the change detection and explanation engine that diffs new filings against prior versions and generates plain‑English summaries of what changed and why it matters
Create the auto‑update system that propagates regulatory changes into living documents (memos, matrices, comparison tables) with cited redlines
Implement the reviewer workflow where compliance teams approve, reject, or modify AI‑generated updates before publication
Ship versioned output with a full audit trail suitable for regulated environments
Validate with real compliance teams at U.S. utilities or energy developers and measure time‑to‑update reduction
Apply GenAI building blocks (prompt engineering, RAG with citation, 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
Document processing pipeline experience: ingestion, parsing, extraction from PDFs, legal filings, or regulatory documents
RAG systems with citation and provenance tracking (not just retrieval, but grounded output with source attribution)
Experience building reliable, auditable AI systems for high‑stakes or regulated environments
Proficiency with GenAI tools and frameworks: prompt engineering, structured extraction, LLM evals, 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 in regulated industries (utilities, energy, financial services, healthcare)
Familiarity with regulatory data sources (FERC, state PUCs, SEC filings, tariff databases)
Experience with document diffing, version control for content, or redline generation
Prior experience building audit trail, compliance workflow, or approval routing systems
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
Compensation
$10,000 - $10,000 a month
Residency Details
This is a 12‑week, on‑site residency in Mountain View, CA ($10K/month). You will work directly with Andrew Ng to take this idea from concept to working product. If the idea validates, you become a co‑founder. AI Fund writes a $1M check at a $4M valuation. We are only considering candidates within commuting distance from Mountain View. As part of the interview process, you will be asked to complete a Builder Challenge.
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AI Fund is Andrew Ng’s venture studio. We identify high-potential applied AI ideas, recruit exceptional builders, and create new companies from scratch. Visiting Engineers join for a 12-week residency in Mountain View to take an idea from concept to working product alongside Andrew and the AI Fund team. If the idea validates, you become a co‑founder. We are backed by a $390M fund from top‑tier global investors. Our purpose is to build AI companies that move humanity forward.
The Idea
STRATA: Regtech copilot that does the work after a new regulation drops.
When a new rule, tariff, or regulatory filing hits, compliance teams don’t just need an alert. They need to understand what changed, figure out the “so what” for their business, and then update a stack of living documents: leadership memos, benchmarking matrices, comparison tables, internal guidance. This work is manual, expensive, and often outsourced to consultants at high cost. Teams in regulated, asset‑heavy industries (utilities, energy, infrastructure) spend 15‑20% of their time on this.
LLMs are excellent at grounded extraction, diffs, and keeping living documents in sync with changing external sources. They struggle at inventing consulting from scratch, but STRATA doesn’t ask them to. The system pulls from trusted primary sources, generates cited redlines and updated cells, routes through a reviewer workflow, and publishes versioned output with an audit trail.
The target vertical is U.S. utilities and energy developers: rate cases, tariffs, interconnection fees.
What you will do
Build the regulatory filing ingestion pipeline that monitors and parses filings from FERC, state PUCs, and relevant regulatory bodies
Develop the change detection and explanation engine that diffs new filings against prior versions and generates plain‑English summaries of what changed and why it matters
Create the auto‑update system that propagates regulatory changes into living documents (memos, matrices, comparison tables) with cited redlines
Implement the reviewer workflow where compliance teams approve, reject, or modify AI‑generated updates before publication
Ship versioned output with a full audit trail suitable for regulated environments
Validate with real compliance teams at U.S. utilities or energy developers and measure time‑to‑update reduction
Apply GenAI building blocks (prompt engineering, RAG with citation, 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
Document processing pipeline experience: ingestion, parsing, extraction from PDFs, legal filings, or regulatory documents
RAG systems with citation and provenance tracking (not just retrieval, but grounded output with source attribution)
Experience building reliable, auditable AI systems for high‑stakes or regulated environments
Proficiency with GenAI tools and frameworks: prompt engineering, structured extraction, LLM evals, 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 in regulated industries (utilities, energy, financial services, healthcare)
Familiarity with regulatory data sources (FERC, state PUCs, SEC filings, tariff databases)
Experience with document diffing, version control for content, or redline generation
Prior experience building audit trail, compliance workflow, or approval routing systems
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
Compensation
$10,000 - $10,000 a month
Residency Details
This is a 12‑week, on‑site residency in Mountain View, CA ($10K/month). You will work directly with Andrew Ng to take this idea from concept to working product. If the idea validates, you become a co‑founder. AI Fund writes a $1M check at a $4M valuation. We are only considering candidates within commuting distance from Mountain View. As part of the interview process, you will be asked to complete a Builder Challenge.
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