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Zscaler is seeking a Principal Software Development Engineer - Agentic Systems to lead the architecture and delivery of large-scale AI/ML infrastructure and production pipelines within the Exposure Management & Security Operations department. This is a hybrid role based in Bangalore, reporting to the Director of Software Development Engineering.
In this role, you will own the architecture and development of scalable AI/ML infrastructure, LLM serving platforms, and agentic workflows tailored for cloud-scale cybersecurity use cases. You will architect reusable platform foundations—including networking, security, authentication, and monitoring—to standardize and secure enterprise AI/ML services. You will define and implement system observability, evaluation, and reliability frameworks to ensure optimal performance and stability of AI systems in production. You will drive cross-functional architectural initiatives in collaboration with product, security, and operations teams to deliver production-grade AI solutions aligned with business goals. You will provide technical leadership and mentorship on distributed systems design while translating complex architectures to non-technical stakeholders to foster alignment across the organization.
Zscaler is a NASDAQ-listed company that accelerates digital transformation through its Zero Trust Exchange platform, protecting thousands of customers from cyberattacks and data loss. The company is building an AI-native enterprise where human potential is amplified by machine intelligence to solve the world's hardest security challenges.
QUALIFICATIONS:
Minimum Qualifications:
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain
- Proven experience designing and operating large-scale, low-latency distributed systems, with deep expertise in availability, fault tolerance, consistency, and cloud-native microservices (AWS preferred, GCP, or Azure)
- Expertise in LLMs and production AI/ML infrastructure, including orchestration frameworks, inference systems, and full-lifecycle pipeline operations
- Demonstrated track record of cross-organizational technical leadership, driving architectural decisions, mentoring teams, and shipping production-grade services
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, backed by a solid foundation in core computer science principles
Preferred Qualifications:
- Hands-on experience architecting autonomous AI agentic workflows and fine-tuning domain-specific LLMs for real-time cybersecurity threat and exposure management
- Proven track record with LLM observability, explainability, and evaluation frameworks in production environments, complemented by serverless architectures for data-intensive workloads
- Deep foundation in core systems, networking, and security architecture for distributed systems, including identity, encryption, access control, VPC, and network security
