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ServiceNow's GAIL (Get AI Live) program deploys engineers directly into strategic customer engagements to drive real AI adoption and measurable value realization. As a Senior in-Market Engineer on the GAIL Core Team, you will own the hardest engagements, set quality standards for the entire practice, and build infrastructure that scales it. This is hands-on, customer-facing work that compounds in impact with every engagement you lead and every engineer you mentor.
Key responsibilities include:
- Lead the most complex GAIL and Go-Live Support engagements — large-scale enterprise deployments, escalations, and high-stakes go-lives where depth and experience matter most.
- Own and evolve the GAIL playbook — keeping deployment standards, required gates, and prescribed sequences current, accurate, and actionable across the program.
- Build, maintain, and push shared GAIL tooling across all engagements — reducing reinvention and raising the floor for every engineer in the rotation.
- Mentor and ramp incoming GAIL engineers through structured onboarding, shadowing, and coaching on first customer interactions.
- Capture patterns from complex deployments and feed them into the team's knowledge base — turning hard-won lessons into reusable assets that proactively uplift the whole team.
- Drive quality standards across the GAIL practice — defining what great looks like and holding the line on it.
- Partner with product and engineering to surface field signal from customer engagements and close the feedback loop.
ServiceNow is the AI control tower for business reinvention, helping 85% of the Fortune 500 work smarter, faster, and better through its AI platform that brings together any AI, any data, and any workflow.
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, when it doesn't, and you 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
- Strong communication skills across technical and non-technical audiences, including customer-facing executive stakeholders
- Business-level Japanese language proficiency (required)
