ServiceNow Senior Technical Consultant - AI

AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation. AtAHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD. We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived. We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives atAHEAD. 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. Roles & Responsibilities Solution and Stakeholder Leadership Translate business outcomes and documented requirements into AI solutions that are secure, governed, explainable, and aligned to platform best practices Identifyand qualify AI use cases with clients, assessing data readiness, deflectionorcycle‑timepotential, risk tolerance, andhuman‑in‑the‑looprequirements. Articulateplainly when a use case is a poor fit for AI. Conduct client and internal demos of Now Assist, AI Agents,AI ControlTowerand agentic workflows, clearly explaining how outputs are produced, where guardrails sit, and what the measured impact is Activelyparticipatein Agile ceremonies, flagging technical andAI‑specificrisks (data quality, hallucination exposure, adoption drag, licensing consumption) during planning Hands-On Development and Delivery Governance Build and extend Now Assist skills, AI Agents, agentic workflows, and orchestration logic; author and tune prompts, tool definitions, and agent instructions against defined success criteria Develop the supporting platform foundation: integrations, Flow Designer and Integration Hub actions, custom tools exposed to agents, Knowledge and catalog data quality, and the taxonomy that AI Search and Now Assist depend on Configure and tune Predictive Intelligence models, Document and Task Intelligence, Virtual Agent and NLU/Conversational Interfaces, and AI Search relevancy Extend AI beyond native capabilities via Generative AI Controller, AI Agent Fabric / MCP, and third‑party LLM or agent integrations where the use case warrants it Establish evaluation discipline: baseline metrics, golden datasets, regression test suites for prompts and skills, A/B and pre/post measurement, and drift monitoring aftergo‑live Enforce responsible‑AI guardrails — data handling and PII scoping, role‑based access to AI capabilities, audit and trace requirements, human approval gates, and configuration in AI Control Tower Safeguard quality through peer reviews, automated tests, and coordinated promotions across dev, test, and prod, including cutover and rollback strategies for AI features Own defect resolution during UAT and hyper‑care, including model and prompt performance issues, driving root‑cause analysis and continuous tuning Team Leadership and Mentoring Coach junior developers on AI fundamentals, prompt and agent design patterns, and the judgment to distinguish a demo from a production ready solution Coordinate daily development tasks, remove roadblocks, and safeguard delivery timelines Facilitate training sessions andknowledge sharingforums that raise AI fluency across the broader delivery team Innovation andCross Product Leadership Lead AI delivery across at least one product suite beyond core platform work, understanding the process being augmented well enough to know where AI genuinely helps Build reusable accelerators — skill libraries, agent patterns, evaluation harnesses, readiness assessments — and drive their adoption across engagements Track each ServiceNow release for new AI capabilities, evaluate themhands‑on, and advise clients on adoption sequencing and licensing implications Contribute lessons learned, benchmarks, and technical articles to internal knowledge bases and external community forums 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 platformexpertise – Integrations, Integration Hub, Flow Designer, Service Portal, UI Builder and Workspaces, imports, plus an architecture mindset for performance, scalability, and clean upgrades Hands‑oncoding – Advanced JavaScript and Glide APIs, REST integrationdesignand consumption, auth schemes, and data pipelines; strong vanilla JavaScript fundamentals with testing habits andversion‑controldiscipline 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 tocontainit 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, vectorsearchand RAG architectures, MCP, cloud platforms, DevOps toolchains, or analytics outside the ServiceNow ecosystem $160,000 - $190,000 a year The compensation range indicated in this posting reflects the On-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount. This OTE range may vary based on the candidate’s relevant experience, qualifications, and geographic location. Why AHEAD: Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between. We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning. USA Employment Benefits include: - Medical, Dental, and Vision Insurance #J-18808-Ljbffr