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ZaniaZaniaSan Francisco, CA

Applied AI Engineer

Builds production AI agents and workflows for governance, risk, and compliance, fine-tuning LLMs on proprietary data for high-accuracy tasks like regulatory analysis and risk assessment. Requires 3+ years applied AI experience with production ML systems emphasizing explainability and responsibility.

180k – 250k/yr
On-site3+ YOEML Engineering

About the role

What you'll do

  • Build & fine-tune models. Fine-tune foundation models on proprietary data and implement novel techniques to achieve world-class accuracy on complex GRC tasks.
  • Develop AI-native workflows. Build sophisticated, multi-step agentic workflows that automate complex GRC processes — from risk assessment to compliance monitoring to evidence collection.
  • Champion responsible AI. Implement and pioneer methods for AI explainability and safety. Our systems must be transparent, auditable, and fair. This is non-negotiable in our domain.
  • Drive innovation. Rapidly prototype, evaluate, and integrate state-of-the-art research (agents, RAG, new architectures) into reliable, production-grade features.

Representative projects

  • Build an AI agent that analyzes thousands of regulatory documents and internal controls, identifying compliance gaps with higher accuracy than a team of human experts.
  • Develop an explainable AI system for risk assessment, allowing auditors and executives to understand and trust the AI's reasoning on high-stakes decisions.
  • Build an advanced RAG pipeline over a massive corpus of unstructured company data to produce precise, verifiable assessments against complex compliance requirements.
  • Partner with GRC subject matter experts to create ground-truth datasets for tasks like third-party risk evaluation, then fine-tune models that become the industry standard.

What you have

  • 3+ years in an applied AI or machine learning engineering role.
  • Proven product sense. You've shipped reliable, production-scale ML products. You know how to use offline evaluation and online experimentation to achieve high-performance results.
  • Hands-on applied AI expertise. Direct experience building with LLMs — fine-tuning, RAG, and agentic systems. Not theoretical. You've put these into production.
  • High agency. You take full ownership of outcomes, move with a bias for action, and have a relentless drive for world-class accuracy. You see constraints as design problems, not blockers.
  • Strong communication. You can work closely with security and GRC research counterparts and articulate technical tradeoffs clearly.

Compensation & benefits

  • Competitive salary + significant equity
  • Flexible PTO
  • Medical, dental, and vision insurance
  • Meals and snacks in the office
  • Relocation and immigration support

Skills

LLMsFine-TuningRAGAgentic SystemsMachine LearningAi ExplainabilityAi SafetyFoundation ModelsPrompt EngineeringEvaluation Metrics

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