Sr. Staff Applied AI Engineer, GTM

Description

The company protects thousands of customers from cyberattacks and data loss through its Zero Trust Exchange platform, a SASE-based, in-line cloud security service running in more than 200 public data centers worldwide plus thousands of private edge sites.

The company treats AI as a way to amplify people and is building an AI-native enterprise to tackle hard security problems.

This is a senior, hands-on AI builder role embedded with the go-to-market organization. You will take unclear, high-stakes ideas and turn them into secure, production-grade tools that move revenue, with success measured in business terms such as pipeline generated and seller productivity.

You will also advise GTM leaders as a transformation partner, running discovery, shaping the GTM AI strategy and roadmap, and guiding Build/Partner/Buy calls. Beyond your own projects, you will improve the technical implementations, standards, and engineering playbooks the wider Applied AI team uses, keeping them current with best practice.

The role reports to the Sr. Manager, Applied AI Engineering in the IT/Data Strategy department and is based in Santa Clara, California, or remote within the US.

Responsibilities

• Work with GTM leaders, RevOps, and product owners from discovery through delivery: map the revenue lifecycle, set the GTM AI roadmap, and advise on feasibility, cost, risk, and Build/Partner/Buy choices.
• Design and ship secure, production-grade AI use cases for revenue teams, using retrieval-augmented generation, structured-data querying, and agentic workflows.
• Treat each solution as a product tied to revenue: build monitoring and evaluation, put security controls around customer and commercial data, and measure ROI against GTM KPIs.
• Drive adoption in the field with Sales Enablement, GTM Operations, and frontline managers by rolling out solutions, training users, and running tight feedback loops based on how sellers actually work.
• Raise the bar for the team by improving and extending shared building blocks such as retrieval pipelines, reference architectures, GTM data connectors, and engineering playbooks, and by mentoring other engineers.

Requirements

• You are comfortable building the path while you walk it and treat ambiguous, fast-changing environments as material to create something useful.
• You act like an owner, with high integrity and a strong bias for action, moving easily between high-level strategy and hands-on execution.
• You are a high-trust collaborator who wants the team to succeed and values candid feedback and mutual respect.
• You are curious about hard technical problems and want to build secure, scalable, and transformative systems.
• You are a pragmatic builder who iterates and ships value quickly without cutting technical quality.
• 5+ years of professional software engineering experience, including 3+ years working directly on AI and/or ML projects.
• Experience driving both AI strategy and execution for GTM functions (Sales, Marketing, Partner Enablement), with solutions shipped to customer-facing teams that had measurable impact on GTM metrics, and a working grasp of the revenue lifecycle.
• Hands-on experience with most parts of modern AI solutions: retrieval methods, reusable skills, agentic orchestration, connecting tools and data through the Model Context Protocol (MCP), and agent-to-agent (A2A) frameworks.
• A record of working directly with GTM leaders on ambiguous problems: running discovery, turning vague expectations into a concrete plan, and explaining trade-offs, risk, and architecture to technical and non-technical audiences.
• Experience securing AI systems and the data they reach, including least-privilege access and defenses against prompt injection, data leakage, and unsafe or non-compliant outputs.
• Strong engineering skills, including deploying and running AI at scale, proficiency in Python, comfort integrating with GTM systems of record, and experience releasing and monitoring AI systems on a major cloud platform.
• Preferred qualifications: proven use of AI technologies and workflows to drive measurable operational efficiency.
• Preferred: GTM experience at a B2B enterprise SaaS or cybersecurity company with complex, multi-motion sales. A prior role in RevOps, Sales Engineering, or GTM Strategy is a strong plus.
• Preferred: direct experience with graph-based knowledge systems and long-term agent memory, such as 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 paired with A/B or holdout experiments that measure business lift in the field.

Conditions

Full-time role. Base pay range is $180,000 - $225,000 USD across US locations, excluding commission, bonus, equity (if applicable), and benefits. Final pay depends on skills, experience, and relevant education or training.

The company complies with applicable federal, state, and local pay transparency rules.

Hybrid working model with on-site presence in Santa Clara, California, or remote for US-based candidates.

The company supports candidates who need accommodations during recruiting, including those who are differently abled, have long-term, mental health, or religious-belief-related needs, are neurodivergent, or need pregnancy-related support.

Benefits

• Various health plans.
• Vacation and sick time plans.
• Parental leave options.
• Retirement options.
• Education reimbursement.
• In-office perks.