Senior Staff Platform Engineer

📋 Job Overview

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.

🏢 About Zscaler

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.

🎯 The Role

We are looking for a Sr. Staff AI Platform Engineer to join our team. This is an On-site role based in Bangalore/Pune, reporting to the Senior Manager in the IT Data Strategy department. In this position, you will design, scale, and maintain enterprise cloud infrastructure and platform capabilities to support production AI/ML workloads. Operating within the IT Data Strategy team, you will drive infrastructure automation, observability, and platform governance while empowering AI and data engineering teams to deliver high-impact solutions reliably and securely.

✅ Key Responsibilities

• Design, build, and maintain scalable, secure, and highly available AWS infrastructure (EKS, Lambda, ECS, VPC, IAM) for AI/ML workloads using Terraform, following IaC best practices including reusable modules, remote state management, and environment-based blueprints
• Own and continuously evolve GitLab CI/CD pipelines for AI platform services, automating build, test, security scanning, and multi-environment deployment workflows to enable fast, reliable, and repeatable releases
• Architect a centralized observability stack using Prometheus and Grafana with golden-signal dashboards across AI/ML services and infrastructure, design intelligent alerting strategies (Alertmanager, PagerDuty, OpsGenie), and lead incident response, root-cause analysis, and postmortems to improve MTTA/MTTR
• Define and track DORA metrics to drive delivery and reliability improvements, while building self-healing, auto-scaling, and cost-optimized infrastructure for AI/ML services (LLM inference, vector databases, agent frameworks) on Kubernetes (EKS)
• Implement infrastructure security best practices, establish platform governance standards, partner with AI/ML and data engineering teams on production-grade AI/RAG deployments, and mentor junior/mid-level engineers through design and code reviews

📌 Required Qualifications

• Demonstrated curiosity and active exploration of AI tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving
• 8+ years of experience as a Platform Engineer / Site Reliability Engineer / DevOps Engineer, including 3+ years supporting AI/ML or data platform infrastructure, with deep hands-on expertise in AWS (EKS, Lambda, ECS, VPC, IAM, S3)
• Strong hands-on experience with Infrastructure as Code using Terraform (modules, workspaces, remote state) and designing/maintaining CI/CD pipelines with GitLab CI/CD (or equivalent), including runners and deployment automation
• Proven expertise in centralized observability using Prometheus and Grafana (custom exporters, dashboard design, alerting rules), along with experience designing and tuning alerting/on-call systems (Alertmanager, PagerDuty, OpsGenie) and owning incident response for production services
• Solid, hands-on understanding of DevOps/DORA metrics (deployment frequency, lead time for changes, change failure rate, MTTR) and how to use them to drive engineering improvement
• Experience deploying and operating containerized applications on Kubernetes (EKS), including Helm charts and autoscaling (HPA, Cluster Autoscaler, Karpenter), combined with strong scripting skills in Python (and/or Go/Bash) and the ability to work independently and lead complex infrastructure initiatives with excellent communication skills befitting a Staff-level engineer

⭐ Desirable Experience

• Experience with LiteLLM (including multi-geo/multi-region deployment patterns), distributed compute frameworks like Ray.io/Anyscale, workflow engines like Temporal, and agentic frameworks such as LangGraph, LangChain, or LlamaIndex
• Working knowledge of vector database platforms (Qdrant, Pinecone, Weaviate), memory/context layers like ZEP, LLMOps/MLOps frameworks and practices (model registry, prompt versioning, feedback loops, MLflow/Kubeflow), and LLM observability/evaluation tooling such as Arize Phoenix
• Exposure to GitOps workflows (ArgoCD/Flux), log aggregation and distributed tracing (Loki, ELK/OpenSearch, Jaeger/Tempo), cloud cost optimization (FinOps), and security/compliance frameworks (SOC 2, ISO 27001) in cloud-native environments

🎁 Benefits

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!

🛂 Visa & Eligibility

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.