- Location
- Remote - USA; San Jose, California, USA · San Jose, California, USA · Remote - USA
- Workplace
- Remote
- Type
- Full-time
- Department
- IT Data Strategy
- Seniority
- Senior
- Experience
- 6+ years
- Source
- Greenhouse
Description
Zscaler (NASDAQ: ZS) accelerates digital transformation so customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange™️ platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Distributed across 160+ public exchanges globally and thousands of private exchanges at the edge, the SASE-based Zero Trust Exchange is the world’s largest in-line cloud security platform.
We believe the future of work is Human + AI and are building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world’s hardest security challenges. Driven by deep customer obsession, we are committed to the mission, outcome, and to each other. We bring these commitments to life through three core behaviors: ownership and collaboration, trust through outcomes and impact, and a challenge culture with ongoing feedback. Ready to make an impact at the company pioneering security transformation in the AI era? Join us at Zscaler.
Role
We are looking for a Staff Applied AI Engineer to join our team. This is an On-site (San Jose, California) or Remote (US) role, reporting to the Manager, Applied AI Engineering in the IT/Data Strategy department. The Staff Applied AI Engineer is a senior, hands-on AI builder embedded with business teams to turn ambiguous, high-stakes ideas into secured, production-grade solutions. Beyond engineering, this person acts as a trusted transformation advisor — running discovery with business leaders, shaping roadmaps, guiding Build/Partner/Buy decisions, and building alongside stakeholders. They also improve and expand the technical implementations, standards, and engineering playbooks the rest of the Applied AI team relies on, keeping the team's deliverables aligned with current best practices.
What you’ll do (Role Expectations)
- Partner with business leaders and product owners from discovery through delivery to map workflows, identify high-value AI opportunities, shape roadmaps, and advise on technical feasibility, cost, and risk
- Design and ship secure, production-grade AI solutions across retrieval-augmented generation, structured data querying, unstructured data mining, and agentic workflows, integrating them with core systems of record
- Bring a product-ownership mindset to deployments by establishing monitoring and evaluation frameworks, implementing least-privilege access, and managing ROI, cost attribution, and support plans
- Set engineering standards by expanding reusable building blocks, reference architectures, skills, and engineering playbooks while mentoring team members
Who You Are (Success Profile)
- You thrive in ambiguity and view dynamic, complex environments as opportunities to build meaningful solutions from the ground up.
- You act like an owner with a strong bias for action, operating with integrity and navigating seamlessly between high-level strategy and hands-on execution.
- You are a high-trust collaborator who embraces a feedback-rich culture, delivering candid insights with clarity and respect to build trust across the team.
- You are driven by innovation, bringing a deep curiosity for complex technical challenges and a passion for building scalable, secure solutions.
- You are a pragmatic builder obsessed with shipping high-quality work, balancing technical excellence with rapid delivery of real business value.
What We’re Looking for (Minimum Qualifications)
- 6+ years of professional software engineering experience, including at least 3 years working directly on AI and/or ML projects
- Hands-on experience across modern AI architecture components, including retrieval methods, reusable skill development, agentic orchestration, Model Context Protocol (MCP) integration, and agent-to-agent (A2A) frameworks
- Proven track record of direct collaboration with business stakeholders to run discovery, translate ambiguous needs into actionable plans, and communicate trade-offs, risk, cost, performance, and architecture
- Demonstrated experience securing AI systems and underlying data, including least-privilege access controls and defending against prompt injection, data leakage, and non-compliant outputs
- Strong engineering foundation proficiency in Python, with experience deploying AI at scale on major cloud platforms (AWS, GCP, Azure), integrating across APIs, relational/vector databases, and enterprise systems, and monitoring production drift and failure modes
What Will Make You Stand Out (Preferred Qualifications)
- Familiarity with memory management and long-term context architectures for AI agents
- Direct experience with graph-based knowledge systems
- Experience building automated evaluation frameworks such as LLM-as-judge methodologies or regression testing at-scale for AI quality
Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.
The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.
At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.
Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:
- Various health plans
- Time off plans for vacation and sick time
- Parental leave options
- Retirement options
- Education reimbursement
- In-office perks, and more!
Learn more about Zscaler's hybrid working model and benefits here.
By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.
Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.
Pay Transparency
Zscaler complies with all applicable federal, state, and local pay transparency rules.
Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.
