Senior Applied AI Engineer
Palo Alto, CAFull-time$180–250K/yrPosted 1y agoStill listed 1w ago
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At a glance
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Job overview
Zania is building agentic AI for governance, risk, and compliance, aiming to replace manual workflows with explainable, production‑grade systems. The senior applied AI engineer will design, fine‑tune, and deploy large language model‑based agents, ensuring accuracy, safety, and transparency while collaborating with security and GRC experts. The role offers in‑person work in Palo Alto with relocation assistance and competitive compensation.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
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:
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Dream Customers: FAANG companies, Big 4 firms, and a portfolio of the world's most notable enterprises.
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Tier 1 Backing: Series A led by NEA, with Anthropic and Menlo Ventures. $18M raised to build a generational company.
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World-Class Team: AI and security leaders from Airbnb, Microsoft, Bain, Deloitte, PwC, Brex, and Instacart.
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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.
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Hyper-Growth: 10x ARR growth in the last year.
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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
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Build & fine-tune models. Fine-tune foundation models on proprietary data and implement novel techniques to achieve world-class accuracy on complex GRC tasks.
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Develop AI-native workflows. Build sophisticated, multi-step agentic workflows that automate complex GRC processes — from risk assessment to compliance monitoring to evidence collection.
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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.
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Drive innovation. Rapidly prototype, evaluate, and integrate state-of-the-art research (agents, RAG, new architectures) into reliable, production-grade features.
Representative projects
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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.
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Develop an explainable AI system for risk assessment, allowing auditors and executives to understand and trust the AI's reasoning on high-stakes decisions.
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Build an advanced RAG pipeline over a massive corpus of unstructured company data to produce precise, verifiable assessments against complex compliance requirements.
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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
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5-8 years in an applied AI or machine learning engineering role.
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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.
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Hands-on applied AI expertise. Direct experience building with LLMs — fine-tuning, RAG, and agentic systems. Not theoretical. You've put these into production.
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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.
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Strong communication. You can work closely with security and GRC research counterparts and articulate technical tradeoffs clearly.
Minimum Qualifications
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Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
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4+ years of experience in applied AI, machine learning engineering, or a related technical role
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Demonstrated hands-on experience building and deploying LLM-based systems (fine-tuning, RAG, or agentic workflows) in a production environment
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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
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Competitive salary + significant equity
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Flexible PTO
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Medical, dental, and vision insurance
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Meals and snacks in the office
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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.
How this job compares
Set against the 6,265 open Machine Learning Engineer jobs on Olive Jobs, counted October 30, 2026.
- Pay
- This posting$180–250K/yr
- California median$175–260K/yr1,383 salary ranges
- US median$144–241K/yr5,015 salary ranges
This range's midpoint, $215K, is close to the California median midpoint ($218K) — in the middle half of Machine Learning Engineer salary ranges in California.
- Openings
- Olive Jobs lists 1,856 open Machine Learning Engineer jobs in California and 6,265 across the US. 7% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 4 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (5,090 postings).
- Education
- 2,545 of the 6,265 open Machine Learning Engineer jobs (41%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 30, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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