Staff Software Engineer: AI Deployment Leader

SmartRecruiters, Inc.; Waltham, Northern (MA, KY); Hybrid; USD 150,000 - 262,000; Full time

Benefits offered by this job

Health plans

401(k) Plan with company match

ESPP

Matching donations

Flexible time away plan

Family leave programs

Job summary

ServiceNow is seeking a Staff Software Engineer for the Get AI Live (GAIL) Core Team. You will own the hardest engagements, set quality standards, and build scalable infrastructure across the program.

This hands-on, customer-facing role requires deep engineering expertise, strong mentoring, and a bias for standardized playbooks to ensure repeatable success across multiple deployments.

Qualifications

• 6+ years of software engineering experience in enterprise/product delivery.
• Experience deploying or integrating AI features and GenAI models in real customer environments.
• Familiarity with prompt engineering and production‑grade outputs.
• Bias for standards over shortcuts and playbook governance.
• Ability to mentor and build reusable tooling for the program.

Responsibilities

• Lead the most complex GAIL engagements and Go‑Live supports—enterprise deployments and high-stakes go‑lives.
• Own and evolve the GAIL playbook with current standards and gates.
• Build, maintain, and push shared GAIL tooling across engagements.
• Mentor and ramp incoming GAIL engineers through onboarding and coaching.
• Capture patterns from deployments and feed into knowledge base for reuse.
• Drive quality standards across the GAIL practice and align with product/engineering.

Skills

Software engineering

AI deployment

GenAI models

Prompt engineering

Mentoring

Tools

Now Assist

AI Agents

Job description

ServiceNow is seeking a Staff Software Engineer for the Get AI Live (GAIL) Core Team. You will own the hardest engagements, set quality standards, and build scalable infrastructure across the program.

This hands-on, customer-facing role requires deep engineering expertise, strong mentoring, and a bias for standardized playbooks to ensure repeatable success across multiple deployments.