SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 164,000 - 205,000 / annual
Zscaler is seeking a technically strong, hands-on Manager of AI & Data Platform Engineering to lead the evolution of the enterprise data platform into an AI-ready data and knowledge platform. This role sits at the intersection of Data Engineering, AI Platform Engineering, Knowledge Engineering, and Generative AI, combining deep expertise in modern data engineering and cloud platforms with practical experience building RAG systems, knowledge graphs, AI/LLM data pipelines, and production-grade AI infrastructure.
You will lead a globally distributed team of data and AI engineers across the US and India, owning performance, career development, and day-to-day execution across full-time staff and contractors. Key responsibilities include:
• Owning the Data Platform (Snowflake, dbt, Matillion) and in-house pipelines that build the enterprise's knowledge and AI foundations, turning structured and unstructured data into trusted, AI-ready assets such as knowledge graphs and vector stores, accountable for quality, reliability, and delivery.
• Translating platform strategy and architecture direction into roadmaps, quarterly plans, and delivered outcomes, partnering with architects and engineering leadership while shifting focus across data, knowledge, and AI work as priorities evolve.
• Running the platform as a product for internal customers (domain delivery teams, BI, context and semantic teams, AI engineering), defining service levels, onboarding paths, and paved roads that enable self-service and AI-native development.
• Building agentic operations that automate the team's operational work, including pipeline monitoring, failure triage, data quality checks, and remediation, establishing reusable frameworks and standards for adoption across teams.
• Diving deep into architectural discussions, removing roadblocks for team members, and evaluating effort estimates while empowering senior and principal engineers to lead system design.
You are an inspiring people leader committed to hiring, mentoring, and advancing engineering team members while cultivating a culture of ownership and engineering excellence. You thrive in a fast-moving AI landscape with an owner's mindset and bias for action.
Zscaler is a NASDAQ-listed company that accelerates digital transformation through its Zero Trust Exchange platform, protecting thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications globally. The company is building an AI-native enterprise where human potential is amplified by machine intelligence.
REQUIREMENTS:
Minimum Qualifications:
• Practical understanding of Generative AI architectures, particularly RAG and enterprise knowledge systems, with experience designing pipelines for structured and unstructured data
• 10+ years of experience in software engineering, data engineering, data platform engineering, or data architecture
• 3+ years of experience leading engineering teams with demonstrated technical and people leadership
• Strong hands-on expertise in Python and SQL, with solid foundation in modern data engineering and distributed systems
• Experience designing and operating production-grade data platforms on AWS (or another major cloud platform) using modern tools such as Snowflake, Databricks, or BigQuery, along with dbt
• Strong grounding in data quality, metadata, lineage, governance, and observability, with proven ability to translate ambiguous problems into scalable engineering solutions
Preferred Qualifications:
• Production experience building RAG or GraphRAG platforms, Knowledge Graphs, and graph databases (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 such as 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 track record of building internal developer platforms and reusable data and AI platform services
