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.
As a Senior AI Platform Engineer, you will design, build, and maintain scalable, secure, and highly available AWS infrastructure optimized for complex AI/ML workloads. Utilizing Terraform and modern IaC principles, you will establish robust cloud architectures, automate release pipelines, and architect comprehensive observability and alerting solutions. Operating with a high degree of autonomy, you will champion platform reliability, security, and governance while partnering with AI/ML teams to deploy production-grade systems and mentor engineers across the organization.
What You'll Do (Role Expectations)- Design, build, and maintain scalable, secure, and highly available AWS infrastructure (EKS, Lambda, ECS, VPC, IAM) for AI/ML workloads using Terraform best practices.
- Own and continuously evolve GitLab CI/CD pipelines for AI platform services to enable fast, reliable, and repeatable automated releases.
- Architect a centralized observability stack using Prometheus and Grafana with golden-signal dashboards and design intelligent alerting strategies to lead efficient incident response.
- 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 on Kubernetes.
- Implement infrastructure security best practices, establish platform governance standards, partner on production-grade AI/RAG deployments, and mentor junior/mid-level engineers.
- You are expert at designing and running production-grade environments, specializing in AWS cloud-native architectures tailored specifically for high-demand AI/ML workloads.
- You are driven to automate everything from infrastructure provisioning to multi-environment code deployment, ensuring systems are repeatable, secure, and easily maintained.
- You rely on concrete observability tools and DORA metrics to diagnose bottlenecks, resolve production incidents, and continuously improve platform reliability and delivery speeds.
- You enjoy working closely with cross-functional AI/ML and data teams to bridge the gap between development and operations, while actively mentoring peers.
- You work exceptionally well independently, taking complete ownership of complex infrastructure initiatives and communicating technical concepts with Staff-level clarity.
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions to optimize outcomes within your functional domain.
- 4+ years of experience as a Platform, SRE, or DevOps Engineer, including 1+ years supporting AI/ML or data platform infrastructure, with deep hands-on AWS skills (EKS, Lambda, ECS, VPC, IAM, S3).
- Strong hands-on experience using Terraform (modules, workspaces, remote state) for Infrastructure as Code and designing/maintaining GitLab CI/CD pipelines with runners and automated deployments.
- Proven expertise in centralized monitoring using Prometheus and Grafana (custom exporters, dashboards, alerting) alongside tuning alerting systems (Alertmanager, PagerDuty, OpsGenie).
- Solid, hands-on understanding of DevOps/DORA metrics (deployment frequency, lead time for changes, change failure rate, MTTR) to measure and drive engineering improvements.
- Experience operating containerized apps on Kubernetes (EKS, Helm, Karpenter/HPA), strong scripting skills in Python (and/or Go/Bash), and excellent communication skills.
- Demonstrate a proven ability to leverage AI technologies and workflows to drive measurable operational efficiency.
- Experience with LiteLLM (multi-region deployments), distributed compute frameworks like Ray.io/Anyscale, workflow engines like Temporal, and agentic frameworks (LangGraph, LangChain, or LlamaIndex).
- Working knowledge of vector databases (Qdrant, Pinecone, Weaviate), memory/context layers like ZEP, MLOps practices (model registry, MLflow/Kubeflow), and LLM observability tools (Arize Phoenix).
- Exposure to GitOps workflows (ArgoCD/Flux), log aggregation and distributed tracing (Loki, ELK, Jaeger/Tempo), cloud cost optimization (FinOps), and security compliance frameworks (SOC 2, ISO 27001).
#LI-Hybrid #LI-NT1
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 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. 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. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.
Pay Transparency
Zscaler complies with all applicable federal, state, and local pay transparency rules.
Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.
Skills Required
- Foundational understanding of AI/ML technologies and experience leveraging, securing, or positioning AI-driven solutions
- 4+ years of experience as a Platform, SRE, or DevOps Engineer
- 1+ years supporting AI/ML or data platform infrastructure
- Deep hands-on AWS experience, including EKS, Lambda, ECS, VPC, IAM, and S3
- Strong hands-on Terraform experience, including modules, workspaces, and remote state
- Experience designing and maintaining GitLab CI/CD pipelines, runners, and automated deployments
- Expertise with Prometheus and Grafana, including custom exporters, dashboards, and alerting
- Experience tuning Alertmanager, PagerDuty, or OpsGenie alerting systems
- Hands-on understanding of DevOps and DORA metrics
- Experience operating containerized applications on Kubernetes, including EKS, Helm, Karpenter, or HPA
- Strong scripting skills in Python, Go, or Bash
- Excellent communication skills
- Ability to leverage AI technologies and workflows for measurable operational efficiency
- Experience with LiteLLM, Ray.io or Anyscale, Temporal, LangGraph, LangChain, or LlamaIndex
- Working knowledge of vector databases, memory/context layers, MLOps practices, or LLM observability tools
- Exposure to GitOps, log aggregation, distributed tracing, FinOps, SOC 2, or ISO 27001
Zscaler Compensation & Benefits Highlights
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Healthcare Strength — Health, dental and vision plans through major carriers, alongside mental-health services, virtual care, and fertility resources, create broad coverage. Feedback suggests coverage breadth and provider choice are seen as strong points.
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Parental & Family Support — Paid parental bonding leave for birthing and non-birthing parents, plus additional disability leave and a phased return option, signals meaningful family support. Feedback suggests these policies contribute to a family-friendly package.
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Equity Value & Accessibility — An ESPP with at least a 15% discount and RSUs for eligible roles add wealth-building potential beyond base pay. Feedback suggests stock programs are a notable strength of the total rewards mix.
Zscaler Insights
What We Do
Zscaler accelerates digital transformation so our customers can be more agile, efficient, resilient, and secure. Our cloud native Zero Trust Exchange platform protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.
Why Work With Us
Our impact comes from how we work—every day, in every decision, as one team. Our values and leadership principles are more than words; they're our operating system. They fuel a culture of execution where trust, transparency, and accountability help us deliver meaningful results for our customers, colleagues, and our company. www.zscaler.com/culture
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Zscaler Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Zscaler's hybrid work environment balances individual employee work styles with best practices to build trust and collaboration – all in support of addressing personal productivity and achieving organizational success.
