Level

ZscalerPosted 6mo ago

Deputy Manager, AI & Platform Engineer

Deputy Manager, AI & Platform Engineer at Zscaler scores 30 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.

Mohali, INDsenior

AI in this role

openai
ragllm-integration

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 160+ public exchanges globally and thousands of private exchanges 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   We are looking for a Deputy Manager, AI & Platform Engineer to join our team. This is a Hybrid role in Mohali, reporting to the Senior Manager – Analytics & Insights in the FP&A department. As Deputy Manager, you will be the technical owner and architect for next-generation Finance AI Platform  - building a secure, extensible internal platform that powers Finance dashboards, workflows, and AI-assisted insights.
What you’ll do (Role Expectations)
  • Architect, build, and own the production-grade AI Platform supporting multiple Finance modules, executive dashboards, and interactive workflows
  • Implement enterprise-grade security, Okta SSO, RBAC mapping, and clean backend API service boundaries for seamless extensibility
  • Manage governed data-serving pipelines, schema design, and caching strategies (API query and semantic caching) to ensure high performance and data fallback reliability
  • Integrate AI assistants via internal LLM gateways and build modular skills & services grounded in Finance context
  • Drive CI/CD release automation via GitLab pipelines while maintaining end-to-end production operations, monitoring, incident response, and system reliability
Who You Are (Success Profile)
  • You are a pragmatic builder with a passion for creating, iterating, and shipping scalable tools that deliver immediate value to users.
  • You are driven by technical innovation and energized by leveraging modern AI technologies to solve complex platform challenges.
  • You are an active problem-solver who enjoys navigating complex data environments to build reliable, high-impact solutions.
  • You act like an owner by balancing strategic architectural vision with hands-on technical execution.
  • You are a high-trust collaborator who builds strong cross-functional partnerships and communicates complex technical concepts with clarity.
What We’re Looking for (Minimum 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
  • 5–8 years building and operating production systems across data, backend, and platform engineering
  • Strong Python (FastAPI/services, pipelines) and SQL (Snowflake/PostgreSQL) expertise
  • Strong AWS fundamentals (VPC/IAM/EC2, security basics) and experience with CI/CD deployment pipelines
  • Experience with authentication and SSO patterns
  • Experience with containerization (Docker) and modern deployment practices
What Will Make You Stand Out (Preferred Qualifications)
  • Hands-on experience with LLM integrations, including OpenAI-compatible APIs, RAG architectures, semantic caching, and prompt/context management
  • Expertise with Snowflake and dbt modeling, standards, testing, CI/CD, Redis caching patterns, and observability best practices
  • Proven track record building internal data applications with React or Streamlit
#LI-Hybrid #LI-HG1

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.

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RagLlm IntegrationOpenAI

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  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How have you integrated a large language model into a production application?
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