Senior Staff Applied AI Engineer, GTM

Zscaler

. Assist GTM AI strategy from discovery through delivery with GTM leaders, RevOps, and product owners .

Posted 10/26/2026full-timeRemote • California • United StatesSenior💰 $180,000 - $225,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI strategy and execution, particularly in GTM functions, with a strong focus on deploying secure AI solutions and improving operational efficiency. Proficient in Python and experienced in integrating AI systems within B2B enterprise environments.

Highest-signal resume keywords

AI Strategy DevelopmentPython ProficiencyGTM Experience in B2B SaaSAI System SecurityDeployment of AI Solutions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAI and ML Project ExperienceRetrieval MethodsAgentic OrchestrationModel Context Protocol (MCP)Agent-to-Agent (A2A) FrameworksAutomated Evaluation FrameworksGraph-Based Knowledge SystemsLong-Term Agent MemoryMonitoring AI Systems

Soft Skills

MentoringCommunicationProblem-SolvingCollaborationChange Management

Tools & Technologies

Cloud PlatformsGTM Systems of RecordRetrieval-Augmented GenerationStructured-Data QueryingEngineering Playbooks

Industry Keywords

GTM AI StrategyRevenue LifecycleB2B EnterpriseCybersecurityRevOps

Tech Stack

Tools & technologies

CloudCyber SecurityPython

About the role

Key responsibilities & impact

Assist GTM AI strategy from discovery through delivery with GTM leaders, RevOps, and product owners
Map the revenue lifecycle and set the GTM AI roadmap
Advise on feasibility, cost, risk, and Build/Partner/Buy decisions
Build and deploy secure, production-grade AI solutions for revenue teams
Design and ship use cases using retrieval-augmented generation, structured-data querying, and agentic workflows
Build monitoring and evaluation frameworks for AI solutions
Implement security controls for customer and commercial data
Establish ROI against GTM KPIs
Drive adoption and change by rolling out solutions, training users, and establishing feedback loops
Improve reusable building blocks such as retrieval pipelines, reference architectures, GTM data connectors, and engineering playbooks
Mentor other engineers
Improve technical implementations, standards, and engineering playbooks for the Applied AI team

Requirements

What you’ll need

5+ years of professional software engineering experience, including 3+ years working directly on AI and/or ML projects
Direct experience driving both AI strategy and execution for GTM functions, including shipping solutions used by customer-facing teams with measurable impact on GTM metrics and fluency in the revenue lifecycle
Hands-on experience with retrieval methods, reusable skill development, agentic orchestration, Model Context Protocol (MCP), and agent-to-agent (A2A) frameworks
Experience working directly with GTM leaders on ambiguous problems, running discovery, creating concrete plans, and communicating trade-offs, risk, and architecture to technical and non-technical audiences
Experience securing AI systems and accessed data, including least-privilege access and protection against prompt injection, data leakage, and unsafe or non-compliant outputs
Strong engineering skills, including deploying and running AI at scale
Proficiency in Python
Experience integrating across GTM systems of record
Experience releasing and monitoring AI systems on a major cloud platform
Proven ability to leverage AI technologies and workflows to drive measurable operational efficiency (preferred)
GTM experience at a B2B enterprise SaaS or cybersecurity company; prior RevOps, Sales Engineering, or GTM Strategy experience is a strong plus (preferred)
Experience with graph-based knowledge systems and long-term agent memory, including account and relationship graphs, GraphRAG, or persistent context across an account’s history (preferred)
Experience building automated evaluation frameworks such as LLM-as-judge or regression testing for AI quality, ideally with A/B or holdout experiments (preferred)

Benefits

Comp & perks

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