Manager – AI & Data Platform Engineering

Job Description

Manager – AI & Data Platform Engineering | Confidential Employer

The Tone:
This is a full-time role at Zscaler, located in Santa Clara, CA (hybrid). Zscaler builds the world’s largest in-line cloud security platform, the Zero Trust Exchange, protecting thousands of customers from cyberattacks and data loss. This role is crucial in evolving the enterprise data platform into an AI-ready data and knowledge platform, amplifying human potential with machine intelligence. It sits at the intersection of Data Engineering, AI Platform Engineering, Knowledge Engineering, and Generative AI, pioneering security transformation in the AI era.

The TL;DR
• Role: Full Time
• Location: Hybrid – Santa Clara, CA
• Pay: $164000–$205000 USD yearly
• Team: Enterprise Data & AI Platform Engineering, reporting to Senior Manager – Data Strategy
• Mission: Lead the evolution of the enterprise data platform into an AI-ready data and knowledge platform.
• Tech Stack: Snowflake, dbt, Matillion, Python, SQL, AWS, Databricks, BigQuery, ArangoDB, Neo4j, Amazon Neptune, LangGraph, LangChain, LlamaIndex, Kubernetes, Terraform, Ray/Ray Data

What You’ll Actually Do
• Lead: Lead a globally distributed team of data and AI engineers, overseeing their performance, career development, and day-to-day execution.
• Own: Own the enterprise data platform and its pipelines, building AI-ready knowledge foundations from structured and unstructured data, ensuring quality and reliability.
• Define: Define and execute platform roadmaps and quarterly plans by translating strategic direction into delivered outcomes, collaborating with architects and leadership.
• Manage: Manage the data platform as an internal product for various customer teams, establishing service levels and self-service paths for AI-native development.
• Automate: Automate operational work through agentic operations, establishing reusable frameworks for tasks like pipeline monitoring, failure triage, and data quality checks.

The Must-Haves
• Background: Manager in AI and Data Platform Engineering with a deep foundation in modern data engineering, cloud platforms, and practical experience building RAG systems, knowledge graphs, and production-grade AI infrastructure.
• Experience: 10+ years in software engineering, data engineering, data platform engineering, or data architecture, including 3+ years leading engineering teams. Experience designing and operating production-grade data platforms on AWS (or another major cloud platform) using tools such as Snowflake, Databricks, or BigQuery, along with dbt.
• Skills: Strong hands-on expertise in Python and SQL, a solid foundation in modern data engineering and distributed systems, and strong grounding in data quality, metadata, lineage, governance, and observability. Practical understanding of Generative AI architectures, particularly RAG and enterprise knowledge systems, with a proven ability to translate ambiguous problems into scalable engineering solutions.
• Bonus: Production experience building RAG or GraphRAG platforms, Knowledge Graphs, and graph databases (e.g., ArangoDB, Neo4j, Amazon Neptune), vector databases, embeddings, hybrid retrieval, and re-ranking. Hands-on experience building infrastructure for AI agents and agentic workflows using frameworks like LangGraph, LangChain, or LlamaIndex, alongside LLM evaluation, AI observability, and LLMOps. Deep cloud-native platform engineering expertise across Kubernetes, Terraform, and Ray/Ray Data, with experience building internal developer platforms and reusable data and AI platform services.