Sr Software Engineer

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

Overview

The AI Application Software Engineer designs, builds, ships, and operates applications whose core behavior is model-driven rather than explicitly authored — conversational and agentic experiences that interpret user intent, reason over context, invoke tools, and act on the user's behalf. In Field Service Management, this means building AI-native experiences for scheduling, dispatch, and service workflows that automate routine work, escalate exceptions, and improve customer outcomes.

This is a hands-on, forward deployed role for a senior engineer whose first instinct is AI — someone who can shape ambiguous customer problems into precise specifications, author the instructions and prompts that govern agent behavior, build the application and integrations around them, and prove through automated evaluation that the result behaves correctly. This is not a machine learning or AI research role; you will not train foundation models. You own what ships, whether a human or an agent produced it.

What You Get to Do

•      Build AI-native applications. Design and ship applications built around agentic behavior across Field Service Management — scheduling, dispatch, and workflows that reason over context, automate routine work, and escalate exceptions.

•      Work AI-first in delivery. Direct coding agents to build, refactor, and test; use AI to think more sharply in front of customers; and apply it as part of everyday engineering practice rather than as a side tool.

•      Deliver forward deployed. Work embedded in customer environments, tuning instructions and evaluation sets on the ground, using AI to compress turnaround without cutting quality.

•      Author and maintain agentic instructions. Write, structure, and version the system instructions, role definitions, tool descriptions, guardrails, and escalation rules that govern agent behavior — treating them as reviewed, regression-covered engineering artifacts.

•      Build automated evaluation and test non-deterministic behavior. Design and operate golden datasets, multi-turn conversation suites, model-as-judge scoring, CI gates, drift detection, adversarial testing, and grounding checks that make change safe.

•      Design conversational experiences. Build experiences that hold context, confirm before consequential actions, and hand off cleanly to humans.

•      Collaborate across product, UX, and documentation. Bring the AI-first instinct into cross-functional partnerships, not just your own code.

•      Own quality and safety in production. Monitor containment, hallucination, prompt injection, and data leakage, then feed failures back into specifications and evaluation sets.

Experience
A demonstrated track record of building, shipping, and operating production software, including hands-on delivery of AI-native application features that real users depend on rather than demos. Direct experience authoring agentic instructions and prompts, designing AI-driven workflows, and building evaluation and testing for non-deterministic behavior is required. Experience with chat experiences is required; voice or multi-channel experience is strongly preferred. Willingness to work directly with customers in a forward deployed capacity is required; prior forward deployed experience is an advantage.

Education
Typically requires a minimum of 5 years of related experience with a Bachelor's degree; or 3 years and a Master's degree; or a PhD without experience; or equivalent work experience.

Key competencies
•      Software engineering fundamentals. Strong command of data structures, algorithms, system design, APIs, data modeling, and testing. Good to have technologies like  HTML, CSS, JavaScript and Java. 

•      AI-native application development. Hands-on experience with agent orchestration at the application layer, tool and function calling, context assembly, grounding against enterprise data, and handling latency, cost, and failure.
•      Agentic instruction and prompt engineering. Demonstrated skill with instructions, role definitions, tool descriptions, guardrails, structured outputs, grounding, citation, graceful failure, and disciplined iteration against measured outcomes.
•      Specification precision. Ability to define a problem rigorously enough that another engineer or an AI agent implements it correctly, and to judge when to solve it in code, in instructions, or by delegating.
•      Customer-facing delivery with AI-native speed. Comfort working directly with customers under real constraints, using AI to cut turnaround, and communicating capability and risk credibly to non-engineers.
•      AI safety and data handling. Working knowledge of prompt injection, data leakage, over-broad tool access, and unsafe autonomous action, translated into concrete guardrails and least-privilege controls.

Desired experience
•      Forward deployed or customer-embedded delivery. Prior work as a forward deployed engineer, solution engineer, or in professional services, delivering software inside a customer's environment.
•      A platform-level view. Experience with agent runtimes, context engineering, retrieval, and memory.
•      Domain depth. Experience in Field Service Management, scheduling, or workforce management is valued but not required; the right engineer can learn the domain.
•      Evaluation and observability tooling. Experience with evaluation frameworks, prompt and instruction management tooling, tracing for LLM applications, and analysis of production transcripts at scale.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

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