Sr. Staff Applied AI Engineer, GTM
New
Z
ZscalerCybersecurity SaaS
On-site in Santa Clara, California or Remote (US role)Full-TimeStaff
Salary180,000 - 225,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years of professional software engineering experience, including 3+ years working directly on AI and/or ML projects
- Required Skills
- PythonArtificial IntelligenceMachine Learning
Requirements
- Bring 5+ years of professional software engineering experience, including 3+ years working directly on AI and/or ML projects.
- Have driven AI strategy and execution for GTM functions such as Sales, Marketing, or Partner Enablement, including shipping solutions used by customer-facing teams with measurable GTM impact.
- Understand the revenue lifecycle and have hands-on experience with retrieval methods, reusable skill development, agentic orchestration, MCP, and A2A frameworks.
- Have worked directly with GTM leaders on ambiguous problems, running discovery and turning unclear expectations into concrete plans.
- Communicate trade-offs, risk, and architecture to technical and non-technical audiences.
- Have experience securing AI systems and their data, including least-privilege access and defending against prompt injection, data leakage, and unsafe or non-compliant outputs.
- Bring strong engineering skills, proficiency in Python, experience integrating GTM systems of record, and experience releasing and monitoring AI systems on a major cloud platform.
- Preferred: experience using AI workflows to drive measurable operational efficiency.
- Preferred: GTM experience in B2B enterprise SaaS or cybersecurity; RevOps, Sales Engineering, or GTM Strategy experience is a plus.
- Preferred: experience with graph-based knowledge systems, long-term agent memory, GraphRAG, or persistent account context.
- Preferred: experience building automated AI evaluation frameworks, such as LLM-as-judge or regression testing, ideally with A/B or holdout experiments.
Responsibilities
- Partner with GTM leaders, RevOps, and product owners to map the revenue lifecycle, shape the AI roadmap, and advise on feasibility, cost, risk, and Build/Partner/Buy decisions.
- Design and ship secure, production-grade AI solutions for revenue teams using retrieval-augmented generation, structured-data querying, and agentic workflows.
- Build monitoring and evaluation frameworks, implement security controls for customer and commercial data, and establish ROI against GTM KPIs.
- Partner with Sales Enablement, GTM Operations, and frontline managers to roll out solutions, train users, and establish feedback loops.
- Improve reusable building blocks, including retrieval pipelines, reference architectures, GTM data connectors, and engineering playbooks.
- Mentor other engineers and help keep team deliverables aligned with current best practices.
View Full Description & ApplyYou'll be redirected to the employer's site
