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 200+ public data centers globally and thousands of private sites 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

As a hands-on Senior AI Engineer within Zscaler's IT AI/ML Engineering team in India, you will design, build, test, and operate production-grade AI applications used by employees and customers globally. Collaborating daily with a US-based technical lead and distributed teammates, you will own well-scoped projects end-to-end, specializing either in agents and retrieval systems or AI business solutions and platform support.

What You'll Do (Role Expectations)

Design and build production-grade AI services, APIs, and retrieval pipelines in Python with clean, tested, and well-documented code.
Lead scoped AI projects from design to launch, breaking down ambiguous business requirements into clear technical tasks.
Integrate test sets, regression checks, tracing, and cost/latency tracking into every feature to ensure system reliability.
Partner closely with global, cross-functional teams, share status transparently, review code, and mentor junior engineers.
Provide L2 support for AI applications, administer enterprise AI platforms, write runbooks, and build automation to reduce repeat issues.

Who You Are (Success Profile)

You take pride in owning a technical project from initial design and prototyping all the way to production monitoring and support.
You are dedicated to clean code, robust testing, data-handling security practices, and raising the collective standards of your team.
You enjoy running structured experiments with models, prompts, and retrieval strategies to turn results into clear, actionable recommendations.
You thrive in global environments, communicating technical concepts clearly in English and working seamlessly across time zones.
You excel at translating complex business problems into reliable, automated AI workflows and user-friendly experiences.

What We're Looking For (Minimum Qualifications)

Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
5+ years of software engineering experience, including 2+ years of hands-on experience building applications with LLMs or ML services.
Bachelor’s or Master’s degree in Computer Science/Engineering (or equivalent experience) with strong Python skills and solid API/service design.
Hands-on experience with prompt design, Retrieval-Augmented Generation (RAG), and function calling or agent frameworks.
Experience evaluating AI systems using test sets, regression checks, and tracing or monitoring tools.
Working knowledge of cloud (AWS, GCP, or Azure), Docker, CI/CD, and experience debugging and supporting production services.

What Will Make You Stand Out (Preferred Qualifications)

Proven ability to leverage AI technologies and workflows to drive operational efficiency, backed by exposure to how AI agents or models are built
Experience with vector/graph databases, embeddings, rerankers, model serving, fine-tuning, or open-weight models.
Familiarity with Model Context Protocol (MCP), tool-integration standards, and agent memory/context management.