Applied AI Engineer

Reposted One Month Ago
Palo Alto, CA, USA
In-Office
180K-250K Annually
Mid level
Artificial Intelligence • Software
The Role
As an Applied AI Engineer, you will create AI systems for Governance, Risk, and Compliance, focusing on accuracy, innovation, and responsible design.
Summary Generated by Built In

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.

Why join:

  • Dream Customers: FAANG companies, Big 4 firms, and a portfolio of the world's most notable enterprises.

  • Tier 1 Backing: Series A led by NEA, with Anthropic and Menlo Ventures. $18M raised to build a generational company.

  • World-Class Team: AI and security leaders from Airbnb, Microsoft, Bain, Deloitte, PwC, Brex, and Instacart.

  • Pioneering Technology: Our engineers and GRC experts work at the absolute forefront of applied AI, building agentic systems that will define the future of compliance.

  • Hyper-Growth: 10x ARR growth in the last year.

  • Competitive Compensation & Equity.

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.

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.

Minimum Qualifications

  • 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.

Skills Required

  • 3+ years of experience in an applied AI or machine learning engineering role
  • Proven track record of shipping reliable, production-scale ML products
  • Hands-on experience building with LLMs, including fine-tuning and agentic systems
  • Demonstrates high-agency and drive for world-class accuracy
  • Exceptional communication skills
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: San Francisco, California
16 Employees
Year Founded: 2023

What We Do

We are transforming Governance, Risk, and Compliance for enterprises and professional service firms using autonomous AI agents. Our solution delivers exceptional accuracy, cuts costs significantly, and shortens a months-long process to just minutes. Achieve compliance more swiftly and with reduced manual effort—enhancing both efficiency and precision.

Similar Jobs

Dialpad Logo Dialpad

Senior Software Engineer

Information Technology
In-Office or Remote
8 Locations
841 Employees
204K-233K Annually
Hybrid
4 Locations
300 Employees
152K-271K Annually

Anthropic Logo Anthropic

Applied AI, Research Engineer

Artificial Intelligence • Natural Language Processing • Generative AI
In-Office
2 Locations
2500 Employees
300K-400K Annually

Antithesis Logo Antithesis

Software Engineer

Information Technology • Software
In-Office
2 Locations
42 Employees

Similar Companies Hiring

Kepler  Thumbnail
Artificial Intelligence • Fintech • Software
New York, New York
9 Employees
Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees
Revel.io Thumbnail
Aerospace • Hardware • Robotics • Software
US
50 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account