Senior Applied AI Engineer
At a glance
Senior AI Engineering role at Zania. San Francisco · full-time · $180,000–$230,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Fine-tune foundation models with proprietary data to improve accuracy on complex governance, risk, and compliance tasks
- Build multi-step AI workflows for risk assessments, compliance monitoring, and collecting supporting evidence
- Make AI decisions explainable, auditable, and fair through practical safety and transparency methods
- Test new agents, retrieval methods, and model architectures, then turn useful findings into reliable production features
- Create systems that review regulatory documents and company controls to find compliance gaps and explain risk assessments
What you bring
- At least four years in applied AI, machine learning engineering, or a closely related technical role
- A bachelor's degree in computer science, engineering, or a related area, or equivalent hands-on experience
- You have deployed LLM systems in production, using fine-tuning, retrieval-augmented generation, or agent workflows
- You have shipped dependable ML products and used offline evaluation and online experiments to improve results
- You communicate technical tradeoffs clearly and can work with GRC specialists and nontechnical stakeholders
Who this fits
This role suits a senior applied AI engineer who has taken LLM systems beyond prototypes and prioritizes accuracy, explainability, and responsible design. The job is based on-site in San Francisco, with relocation assistance available.
From the employer
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
5-8 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
4+ 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.