Scope: As a Senior Technical Consultant focused on AI capabilities, you will own the end-to-end build of AI-enabled solutions on the Now Platform — Now Assist skills and AI Agents through predictive models, AI Search, and the data foundations that make them work. You will guide development activities, mentor technical consultants and junior developers, and partner with Principal consultants and architects to shape complex agentic solutions. Beyond core platform development, you will lead AI enablement across at least one additional product suite (ITSM, ITOM, ITAM, SecOps, IRM, CSM, HRSD, SPM, or ESM) and translate ambiguous business outcomes into secure, governed, measurable AI capabilities. Your depth in both platform engineering and applied AI will influence how our clients adopt agentic workflows and how they realize value from them.
Opportunity Stage: Resources are needed ASAP.
Qualifications
- 6+ years in the ServiceNow domain, with meaningful recent time spent building AI-enabled solutions in production
- ServiceNow AI depth – Now Assist, AI Agent Studio and AI Agent Orchestrator, Now Assist Skill Kit, AI Search, Predictive Intelligence, Document/Task Intelligence, Virtual Agent and NLU, AI Control Tower, and Generative AI Controller
- Data foundation fluency – Understands that AI outcomes track data quality; comfortable with Workflow Data Fabric, CMDB/CSDM health, knowledge governance, and taxonomy design as prerequisites rather than afterthoughts
- Core-platform expertise – Integrations, Integration Hub, Flow Designer, Service Portal, UI Builder and Workspaces, imports, plus an architecture mindset for performance, scalability, and clean upgrades
- Hands-on coding – Advanced JavaScript and Glide APIs, REST integration design and consumption, auth schemes, and data pipelines; strong vanilla JavaScript fundamentals with testing habits and version-control discipline
- Applied AI craft – Prompt engineering and iteration, retrieval and grounding patterns, tool/function calling, agent decomposition and orchestration, and a working grasp of where LLMs fail and how to contain it
- Evaluation and measurement rigor – Defines success metrics before building, tests systematically, and reports honest results including negative ones
- Responsible AI judgment – Practical command of data privacy, access control, auditability, bias and hallucination risk, and the governance conversations that come with them
- Product depth – Proven leadership in at least one suite beyond core ITSM and Service Portal
- Collaborative mentor and lifelong learner – Explains AI concepts simply to non-technical stakeholders, calibrates expectations against hype, and stays current in a space that changes quarterly
- ServiceNow certifications – CSA, CAD, CIS, and AI-related micro-certifications are welcome, though demonstrated hands-on expertise is valued more highly than credentials
- Broader tech stack awareness – Familiarity with LLM providers and APIs, vector search and RAG architectures, MCP, cloud platforms, DevOps toolchains, or analytics outside the ServiceNow ecosystem