Staff Applied AI Engineer

Zscaler

21d•Hybrid

About The Position

Zscaler accelerates digital transformation so our customers can be more agile, efficient, resilient, and secure. Our cloud native Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location. Here, impact in your role matters more than title and trust is built on results. We believe in transparency and value constructive, honest debate—we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession, collaboration, ownership and accountability. We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges and want to make a positive difference on a global scale, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity. Our general and administrative teams help to support and scale our great company. Whether striving to grow our workforce, nurture an amazing culture and work environment, support our financial and legal operations, or maintain our global infrastructure, the G&A team provides a strong foundation for growth. Put your passion, drive and expertise to work with the world’s cloud security leader. We’re looking for an experienced Staff-level Applied AI Engineer to join our IT AI/ML Engineering team. This role offers flexibility to work remotely within the United States, with a preference for candidates based near our San Jose, CA office who can participate in a hybrid schedule (3 days per week onsite). Reporting to the Manager of Applied AI Solutions Engineering, you will be responsible for: Developing and implementing end-to-end AI solutions to enhance productivity and optimize decision-making across the organization Designing AI lifecycle management strategies with automated observability, CI/CD workflows, and robust testing frameworks Collaborating with cross-functional teams to identify AI opportunities and translate them into technical requirements Mentoring team members, conducting architecture/code reviews, and supporting AI governance policies for ethical and efficient AI use Building scalable, cloud-based AI pipelines leveraging state-of-the-art technologies

Requirements

6+ years of professional software engineering experience, including 3+ years focused on AI/ML projects
Bachelor’s degree in computer science, software engineering, data science, or related field
Proficiency in Python and SQL, with experience designing, building, and deploying production-grade AI/ML solutions
Experience with cloud platforms (AWS, GCP, or Azure) and familiarity with MLOps/AI DevOps tools (e.g., MLflow, Kubeflow)
Expertise with CI/CD pipelines, model observability, and scalable architectures

Nice To Haves

Prior experience deploying scalable and secure AI solutions for real-world use cases
Proficiency in fine-tuning LLMs, Retrieval-Augmented Generation (RAG), and technologies like Langchain or Langgraph, GraphRAG, and Model Context Protocol
Knowledge of AI lifecycle management, governance frameworks, and strategies for monitoring and retraining models

Responsibilities

Developing and implementing end-to-end AI solutions to enhance productivity and optimize decision-making across the organization
Designing AI lifecycle management strategies with automated observability, CI/CD workflows, and robust testing frameworks
Collaborating with cross-functional teams to identify AI opportunities and translate them into technical requirements
Mentoring team members, conducting architecture/code reviews, and supporting AI governance policies for ethical and efficient AI use
Building scalable, cloud-based AI pipelines leveraging state-of-the-art technologies