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Salary: USD 149,800 - 262,200 / annual
ServiceNow is seeking a Staff Software Engineer to join the GAIL (Get AI Live) Core Team, a permanent engine that drives real AI adoption and measurable value realization across strategic customer engagements. This is a hands-on, customer-facing role where you will own the most complex enterprise deployments, set quality standards for the entire practice, and build infrastructure that scales impact.
In this role, you will lead large-scale enterprise deployments, escalations, and high-stakes go-lives where depth and experience matter most. You will own and evolve the GAIL playbook, keeping deployment standards, required gates, and prescribed sequences current and actionable across the program. You will build, maintain, and push shared GAIL tooling across all engagements, reducing reinvention and raising the floor for every engineer in the rotation.
You will mentor and ramp incoming GAIL engineers through structured onboarding, shadowing, and coaching on first customer interactions. You will capture patterns from complex deployments and feed them into the team's knowledge base, turning hard-won lessons into reusable assets. You will drive quality standards across the GAIL practice, defining what great looks like and holding the line on it. You will also partner with product and engineering to surface field signal from customer engagements and close the feedback loop.
This is not theoretical process work—it is hands-on, customer-facing work that compounds in impact with every engagement you lead and every engineer you bring up behind you.
REQUIREMENTS:
- 6+ years of software engineering experience, ideally with a mix of enterprise product work and 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
- The ability to mentor effectively; you raise the level of the engineers around you through direct coaching, not just example
- Strong communication skills across technical and non-technical audiences, including customer-facing executive stakeholders
