Job Description

Engineer in Residence, AI Regulatory Intelligence & Operations

Regulated companies receive a constant stream of rules, filings, standards, and guidance, while interpreting changes and proving compliance remains manual. Teams need to know what changed, which obligations are affected, who owns the response, and what evidence will satisfy an audit. This role is to build an AI-native regulatory intelligence and operations system, starting with an AI Fund and AES co-build.

What You'll Build

• A regulatory-source pipeline with versioning, provenance, citations, and change detection.
• An obligation and impact-mapping system connecting changes to policies, controls, assets, and workflows.
• An operations workspace that assigns owners, tracks remediation, and collects the evidence needed for review or audit.
• A trust layer with human approval, traceable reasoning, access controls, and evaluation of missed or unsupported obligations.

What You'll Do

• Own the build across ingestion, retrieval, structured extraction, impact mapping, workflow orchestration, and deployment.
• Work with AI Fund and domain users to define the first regulatory workflow, pilot scope, success metrics, and MVP cut line.
• Design a system that keeps source evidence and uncertainty visible at every important decision point.
• Build evals for change detection, obligation extraction, citations, missed requirements, and workflow completion.
• Make infrastructure and security choices that support a fast pilot without blocking enterprise scale or auditability.

What You Need

• Strong full-stack or backend engineering across data pipelines, workflows, APIs, and enterprise systems.
• Demonstrated experience building GenAI products with retrieval, structured extraction, tool use, evals, citations, and guardrails.
• Experience with regulated data, compliance workflows, policy operations, risk systems, or other evidence-sensitive products.
• Product judgment for systems where precision, provenance, access control, and human review determine whether users can trust the output.
• You know how to use AI coding assistants and modern AI tools to accelerate implementation without weakening engineering judgment.
• US work authorization. We are unable to sponsor visas for this role.

Helpful But Not Required

Experience in energy, infrastructure, financial services, healthcare, legal technology, or another regulated industry.

Experience with knowledge graphs, document intelligence, audit systems, or policy-management platforms.

Founder or founding engineer experience shipping enterprise software from zero to one.

Who This Is For

A builder who wants to turn regulatory intelligence into operational decisions and completed work.

Someone who understands that citations, controls, and human review are core product features in regulated environments.

What To Know Upfront

• This is a 12-week, full-time, on-site residency in Mountain View, California.
• Not every residency becomes a company. The goal is to pressure-test the idea quickly and honestly with real users and customers.
• You will be building an AI Fund idea, not bringing your own startup idea into the program.
• The process typically includes a Builder Event or equivalent working conversation, then a 48-hour Builder Challenge, then panel review with AI Fund build leadership.
• The compensation is intentionally modest during the residency because the upside, if the idea works, is a founder-level role.

Compensation

$10,000/month for 12 weeks ($30,000 total). This is a contract role during the residency. If the build leads to a funded company, the next step is a founder-level role with meaningful equity upside.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.