# Robert Half — AI Adoption Lead

- Generated: 2026-08-25 10:58:30 AM EDT
- Original/canonical posting: https://www.linkedin.com/jobs/view/4457198232/
- Posted: 14 hours ago at capture time
- Applicants: 44 applicants
- Work model/location: North Carolina; remote status not disclosed
- Employment type: Full-time
- Compensation: Not disclosed
- Travel: Not disclosed
- Positioning track: Technical manager
- Fit outcome: FAIL — 71%

## Direct-match strengths

AI strategy, team building, LLMs, RAG, agents, Python, SQL, APIs, forecasting, automation, and enterprise adoption are strong.

## Hard or material gaps

Hard work-model conflict: the posting is located in North Carolina and does not establish remote eligibility. The role also centers ITSM/service-desk platforms and requires breadth across ServiceNow, Zendesk, Remedy, PyTorch, Scikit-learn, feature stores, and recommendation engines that Keith's sources do not establish.

## Weighted evidence map

1. AI strategy and team leadership — 3/3: Direct roadmaps and teams up to 25.
2. LLMs, RAG, agents, Python, and APIs — 3/3: Direct production evidence.
3. Predictive analytics and forecasting — 3/3: Direct SuccessKPI and AWS evidence.
4. IT operations transformation — 2/3: Adjacent automation/platform work.
5. ITSM/service-desk product depth — 1/3: No documented ownership of this function.
6. Named ITSM and ML tool breadth — 1/3: Jira is supported; several required platforms/libraries are not.
7. Eligible work model — 0/3: North Carolina listing without remote status conflicts with constraints.

## Keyword diagnostic

No resume generated. Strong AI/agent/RAG overlap is offset by location and mandatory ITSM/platform breadth.

## Full normalized job description

We are seeking an innovative
AI Team Lead
to spearhead the adoption of Artificial Intelligence across IT Service Management (ITSM), Application Support, and Enterprise Operations. This leadership role is responsible for defining the vision, strategy, and execution of AI-powered solutions that transform how technology services are delivered, supported, and continuously improved.
As the AI leader for IT Operations, you will build and lead a high-performing team of AI Engineers, Data Scientists, and Machine Learning Engineers focused on modernizing service desk operations through Generative AI, Machine Learning, Predictive Analytics, Intelligent Automation, and Agentic AI solutions.
This role is ideal for someone who thrives in ambiguous environments, can create a roadmap where one does not exist, and has a demonstrated ability to partner with executive leadership, IT operations teams, and business stakeholders to identify opportunities where AI can reduce operational costs, improve service quality, accelerate issue resolution, and enhance both employee and customer experiences.
You will serve as the organization's AI champion, driving the evolution from traditional support models to intelligent, AI-assisted operations.
Design, develop, train, test, and deploy machine learning models that automate ticket classification, routing, prioritization, escalation, and resolution workflows.
Build AI-powered Service Desk Copilots, intelligent virtual agents, and support assistants leveraging OpenAI, Claude, Gemini, Azure OpenAI, and other modern LLM platforms.
Develop Retrieval-Augmented Generation (RAG) solutions that leverage IT knowledge bases, runbooks, support documentation, and operational procedures.
Write production-grade code using Python, SQL, APIs, and AI frameworks including LangChain, LangGraph, TensorFlow, PyTorch, and Scikit-learn.
Engineer scalable AI pipelines, feature stores, vector databases, and model-serving architectures to support enterprise-scale deployments.
Develop autonomous and semi-autonomous AI agents capable of performing operational tasks, resolving common incidents, and orchestrating workflows across IT systems.
Build recommendation engines, anomaly detection models, root-cause analysis solutions, workload forecasting models, and predictive incident prevention platforms.
Fine-tune, evaluate, monitor, and optimize Large Language Models and machine learning models to improve support outcomes and user experiences.
ITSM & Application Support Transformation
Perform deep analysis of service desk operations, application support functions, incident trends, and ticketing data to uncover opportunities for automation.
Integrate AI capabilities into ServiceNow, Jira Service Management, Zendesk, Freshservice, Remedy, and custom enterprise platforms.
Develop intelligent solutions that reduce ticket volumes, shorten Mean Time to Resolution (MTTR), and improve First Contact Resolution (FCR) rates.
Create AI-powered knowledge management systems that automatically generate, categorize, summarize, and surface support content.
Leverage NLP techniques to analyze incidents, system logs, call transcripts, emails, chats, and support tickets to identify patterns and operational risks.
Build predictive analytics solutions that proactively identify service disruptions, recurring incidents, application failures, and infrastructure issues before business impact occurs.

## Artifact metadata

- Resume and cover letter: Not generated under the fit gate.
- LinkedIn connection note: Not generated for a FAIL role.
- Google Drive used: No