Principal AI Platform Engineer

ServiceNow•Santa Clara, CA

1d•$221,200 - $387,100

About The Position

This senior, customer-facing engineering role leads the technical direction of the Forward Deployed Engineering (FDE) group within ServiceNow’s CRM & Industry Engineering organization. The engineer works directly with customers to understand their business processes, data, and AI goals; translate ambiguous needs into well-scoped agentic AI use cases; design solutions on the ServiceNow platform; and guide those solutions through deployment into production. As the group’s most senior technical member, this role establishes architecture, technical strategy, reusable deployment patterns, and solution accelerators for use across customer engagements. It owns the correctness, reliability, safety, and business outcomes of delivered agentic systems, while advising customer stakeholders on capabilities, limitations, tradeoffs, and responsible adoption. The role also mentors engineers, verifies deployed systems, and shares field learnings with ServiceNow product and engineering teams to improve the platform.

Requirements

Demonstrated experience designing, deploying, and operating production software and AI solutions in customer-facing settings, including leading complex engagements to successful business outcomes.
Recognized technical authority with the autonomy to set multi-engagement technical strategy and architecture standards, drive an agenda aligned with organizational goals, navigate ambiguity, and coach senior engineers.
Extensive experience working directly with customers to analyze needs, architect solutions, and deploy them to production in a forward-deployed, professional services, solution architecture, or comparable delivery role.
Hands-on experience designing and operating autonomous agent systems, including planning, tool invocation, memory, context design, and guardrails.
Working knowledge of LLM behavior, evaluation, and failure modes sufficient to reason about and verify agentic systems in production.
Expert-level system design and solution architecture skills, including end-to-end design across systems and data, sequencing decisions under uncertainty, build-versus-buy-versus-configure judgments, and reusable architectural patterns.
Working knowledge of security and reliability risks in AI-integrated systems and how to address them through concrete, least-privilege practices, monitoring, and rollback.
Excellent communication and stakeholder skills, including the ability to lead discovery and working sessions, influence technical and executive audiences, and explain capabilities, limitations, tradeoffs, and risk.
Record of leading and coaching engineers, including senior engineers, setting reusable standards across teams, and improving a group’s delivery capability.
Bachelor’s degree in computer science, software engineering, or a related technical field, or equivalent practical experience.
15 years of related experience with a bachelor’s degree in computer science; or 12 years with a master’s degree; or a PhD with 8 years of experience; or equivalent experience.

Nice To Haves

Knowledge of the ServiceNow platform and the CRM & Industry domains served by the role, including sales automation, CPQ, customer service, and field service.
Advanced degrees or relevant certifications.

Responsibilities

Work with customer business and technical teams to understand processes, data, and goals across sales automation, CPQ, customer service, and field service, and translate needs into clearly scoped agentic AI use cases with success criteria.
Design agentic AI solutions on the ServiceNow platform, including agent workflows, integrations, data and context design, and guardrails.
Build, configure, integrate, validate, and deploy solutions into customer production environments.
Define technical direction, reference architectures, reusable deployment patterns, and solution accelerators for the FDE group.
Advise customers as a senior technical partner, communicating agentic AI capabilities, limitations, tradeoffs, and responsible adoption practices.
Verify the correctness, security, reliability, and safety of deployed agents; test edge cases and failure modes; address risks such as prompt injection and data leakage; and establish monitoring and rollback for behavioral drift.
Provide architectural direction, technical reviews, mentorship, and support for engineers across engagements, including resolving difficult technical problems.
Share recurring use cases, platform gaps, and customer feedback with ServiceNow product and engineering teams.