Applied AI Engineer

About the role

You will build AI systems designed to outperform the world's leading experts in Governance, Risk, and Compliance. Not research. Not prototypes. Production systems with a fanatical focus on accuracy, explainability, and responsible design. You will own the AI-native products that set a new global standard for GRC. We use an in-person work model and offer relocation assistance.

Responsibilities

• 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.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
• 3+ years of experience in applied AI, machine learning engineering, or a related technical role
• Demonstrated hands-on experience building and deploying LLM-based systems (fine-tuning, RAG, or agentic workflows) in a production environment
• Strong written and verbal communication skills - you will collaborate closely with GRC subject matter experts and must translate technical tradeoffs clearly to non-technical stakeholders
• Compensation & benefits
• Competitive salary + significant equity
• Flexible PTO
• Medical, dental, and vision insurance
• Meals and snacks in the office
• Relocation and immigration support
• Zania is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

Benefits

Additional Information

Why Zania Every enterprise spends millions on Governance, Risk, and Compliance. It's one of the most critical - and most painful - parts of running a business. The industry has been dominated by legacy platforms with notoriously low NPS scores for decades. It's completely ripe for disruption. Zania is building agentic AI for GRC to solve this problem. We're building intelligent agents that execute complex risk and compliance workflows with full explainability - not dashboards, not copilots, but agents that do the work. We've found exceptional product-market fit and are scaling fast.

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