Sr. Staff Software Development Engineer - AI Platform

About this role

About Zscaler

Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our 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 say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. 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 be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.

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.

What you’ll do (Role Expectations)

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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

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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

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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

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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)

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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

Who You Are (Success Profile)

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You act like an owner with a passion for the mission, operating with integrity and navigating seamlessly between high-level platform strategy and hands-on execution.

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You are a high-trust collaborator who is ambitious for the overall team, fostering an open feedback culture delivered with clarity and respect to build lasting trust.

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You are driven by innovation and deep technical curiosity, continuously seeking secure, scalable, and modern solutions to complex platform engineering challenges.

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You champion simplicity by distilling complex technical architecture, user needs, and operational concepts into clear, actionable plans and focused communication.

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You are data-driven, leveraging analytics and measurable metrics to guide informed engineering decisions, evaluate truth, and optimize reliability.

What We’re Looking for (Minimum Qualifications)

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Demonstrated curiosity and active exploration of AI tools, with a proven history of integrating new technologies to enhance daily workflows and augment problem-solving

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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)

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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

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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

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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

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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

What Will Make You Stand Out (Preferred Qualifications)

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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,…