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Salary: USD 128,900 - 219,100 / annual
ServiceNow is seeking a Staff Software Engineer to join the GAIL (Get AI Live) Core Team, the permanent foundation behind their customer-facing AI adoption program. This is a hands-on, customer-facing role where you will own the most complex enterprise deployments, set quality standards across the practice, and build shared infrastructure that scales impact.
In this role, you will lead large-scale enterprise AI deployments and go-live support engagements where depth and experience are critical. You'll own and evolve the GAIL playbook, ensuring deployment standards and prescribed sequences remain current and actionable. You will build and maintain shared tooling used across all engagements, reducing reinvention and raising the baseline for every engineer in the rotation.
Mentorship is central to this position: you'll ramp incoming GAIL engineers through structured onboarding, shadowing, and coaching on their first customer interactions. You'll capture patterns from complex deployments and feed them into the team's knowledge base, turning hard-won lessons into reusable assets. You'll drive quality standards across the GAIL practice, defining what excellence looks like and holding the line on it. Finally, you'll partner with product and engineering teams to surface field signal from customer engagements and close the feedback loop.
This is not theoretical process work—it's hands-on engineering that compounds in impact with every engagement you lead and every engineer you develop.
Requirements:
- 4+ years of software engineering experience, ideally combining enterprise product work with hands-on customer or field delivery
- Strong coding ability in JavaScript and one or more additional languages (Java, Python, or equivalent), with a track record of building and shipping production-quality solutions
- Experience deploying or integrating AI features and GenAI models—including Now Assist, AI Agents, or equivalent platforms—in real customer environments
- Familiarity with prompt engineering and the judgment to tune non-deterministic outputs for reliability and production-grade clarity
- A bias for standards over shortcuts; you know when a playbook gate applies and own that call with clear reasoning
- A builder's instinct for shared tooling and reusable patterns; you don't reinvent the wheel when you can build something the whole program can use
- Ability to mentor effectively; you raise the level of engineers around you through direct coaching, not just example
- Strong communication skills across technical and non-technical audiences, including customer-facing executive stakeholders
