Manager – AI & Data Platform Engineering

Zscaler

. Lead a 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 .

Posted 11/11/2026full-timeRemote • California • United StatesSeniorLead💰 $164,000 - $205,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading data and AI engineering teams, with a strong focus on building and operating data platforms using Snowflake, dbt, and cloud-native technologies. Proven ability to translate complex data challenges into scalable solutions while ensuring data quality and governance.

Highest-signal resume keywords

Data Platform EngineeringGenerative AI ArchitecturesPython and SQL ExpertiseCloud Platform ExperienceTeam Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSoftware EngineeringData ArchitectureProduction-Grade Data PlatformsData QualityMetadata ManagementGraph DatabasesAI WorkflowsKubernetesTerraform

Soft Skills

Technical LeadershipPeople LeadershipProblem Solving

Tools & Technologies

SnowflakeDbtMatillionAWSDatabricksBigQueryLangGraphLangChainLlamaIndexRay

Industry Keywords

Generative AIKnowledge GraphsData GovernanceObservabilityHybrid Retrieval

Tech Stack

Tools & technologies

AWSBigQueryCloudDistributed SystemsKubernetesMatillionPythonRaySnowflakeSQLTerraform

About the role

Key responsibilities & impact

Lead a 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
Own the Data Platform using Snowflake, dbt, and Matillion
Build enterprise knowledge and AI foundations by turning structured and unstructured data into trusted AI-ready assets such as knowledge graphs and vector stores
Own platform quality, reliability, and delivery
Turn platform strategy and architecture direction into roadmaps, quarterly plans, and delivered outcomes
Partner with architects and engineering leadership and shift focus across data, knowledge, and AI work as priorities change
Run the platform as a product for internal customers, defining service levels, onboarding paths, and paved roads
Build agentic operations to automate pipeline monitoring, failure triage, data quality checks, and remediation
Establish reusable operational frameworks and standards for other teams

Requirements

What you’ll need

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 a 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 Snowflake, Databricks, or BigQuery, along with dbt
Strong grounding in data quality, metadata, lineage, governance, and observability
Proven ability to translate ambiguous problems into scalable engineering solutions
Production experience building RAG or GraphRAG platforms, knowledge graphs, graph databases, vector databases, embeddings, hybrid retrieval, and re-ranking
Hands-on experience building infrastructure for AI agents and agentic workflows using LangGraph, LangChain, or LlamaIndex, alongside LLM evaluation, AI observability, and LLMOps
Deep cloud-native platform engineering expertise across Kubernetes, Terraform, and Ray/Ray Data
Track record of building internal developer platforms and reusable data and AI platform services

Benefits

Comp & perks

Various health plans
Time off plans for vacation and sick time
Parental leave options
Retirement options
Education reimbursement
In-office perks
Comprehensive and inclusive benefits for employees and their families
Reasonable support/accommodations in recruiting processes