Senior Machine Learning Engineer (Agentic AI)

• Independently develop and implement machine learning models and Generative AI solutions, with a strong emphasis on building and deploying Agentic AI architectures
• Drive the end-to-end productionization of AI agents, navigating the complexities of multi-step reasoning, tool use, state management, and LLM orchestration in live environments
• Design and implement advanced LLMOps frameworks, ensuring deep observability, rigorous monitoring, logging, and evaluation specifically tailored for dynamic AI agents
• Assist in refining and optimizing both modern GenAI pipelines and existing classical ML models (feature engineering, hyperparameter tuning) for maximum accuracy, efficiency, and scalability
• Collaborating with cross-functional teams to translate complex business needs into technical solutions

Who You Are (Success Profile)

• You thrive in ambiguity and are comfortable building the path as you walk it, seeing dynamic environments as the raw material to build something meaningful
• You act like an owner with a passion for the mission and a bias for action, navigating seamlessly between high-level strategy and hands-on execution
• You are a problem-solver who seeks out challenges because you are energized by finding solutions that deliver the biggest impact
• You are a learner with a growth mindset, actively seeking feedback to become a better partner and a stronger teammate
• You are driven by innovation and have a deep curiosity for how things work, believing in the power of technology to accelerate transformation

What We’re Looking for (Minimum Qualifications)

• 3 to 5 years of related experience as an MLE, with a strong track record of building and deploying ML systems
• Proven hands-on experience in creating Gen AI-based systems, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and a clear history of operationalizing Agentic AI in production
• Deep understanding of MLOps and LLMOps principles, specifically dealing with the unique monitoring, observability, and debugging challenges of non-deterministic AI agents
• A solid computer science foundation (data structures, algorithms) coupled with expertise in Python (scikit-learn, PyTorch/TensorFlow) and SQL for comprehensive feature engineering and model evaluation
• Excellent communication and interpersonal skills, with the ability to work independently and as a strong team player

What Will Make You Stand Out (Preferred Qualifications)

• Expertise with cloud services such as AWS, GCP, or Azure and ML platforms like Kubeflow or SageMaker
• Familiarity with systems programming or distributed systems
• A demonstrated interest in innovation, such as participation in tech blogs, external papers, or industry knowledge-sharing

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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 Future of Work strategy, 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. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.