Visiting Engineer: STRATA
AI Fund | Mountain View, California, United States | Yesterday
$10,000/mo| contract | on-site | entry
skills: generative ai, document processing, rag, prompt engineering, python, backend development, frontend development, ai assisted coding, scalable ai systems, api development, prompt engineering, r
rag with citation, agentic frameworks, llm evals, guardrails, microservices, event-driven architectures, datastore design
Visiting Engineer: STRATA
Mountain View, CA
AI Fund – AI Fund /
Contract /
On-site
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 US utilities and energy developers: rate cases, tariffs, interconnection fees.
What you will do:
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Mountain View, CA
AI Fund – AI Fund /
Contract /
On-site
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 US 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 US 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
- 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
- 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
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.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Benefits
co-founder opportunity · seed funding
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