AI Implementer

Mobileye

. Lead the company-wide rollout of development and productivity tools, including AI coding assistants, enterprise copilots, chat and agent platforms: evaluation, deployment, licensing, access provisioning, onboarding and adoption across all departments .

Posted 11/4/2026full-timeJerusalem • IsraelMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the deployment of AI tools and automation across departments, with a strong focus on integrating enterprise systems and ensuring security and governance. Proficient in scripting, DevOps practices, and collaborating with both technical and non-technical stakeholders.

Highest-signal resume keywords

DevOpsAI Tools DeploymentScripting/ProgrammingREST APIs IntegrationCommunication Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ScriptingProgrammingLLMs/GenAIREST APIsJSONDockerKubernetesCI/CDGitTroubleshooting

Soft Skills

Strong Communication

Tools & Technologies

JiraConfluenceSharePointJenkinsMicrosoft 365ServiceNowAzureAWSMCPAI Platforms

Industry Keywords

ITSMAutomationSecurity Best PracticesIdentity & Access ManagementCost Monitoring

Tech Stack

Tools & technologies

AWSAzureDockerITSMJenkinsKubernetesLinuxServiceNowVault

About the role

Key responsibilities & impact

Lead the company-wide rollout of development and productivity tools, including AI coding assistants, enterprise copilots, chat and agent platforms: evaluation, deployment, licensing, access provisioning, onboarding and adoption across all departments
Design, build and deploy AI agents, assistants and automations for IT and different business units
Develop and maintain MCP server integrations, including Jira, Confluence, SharePoint, Jenkins and Microsoft 365, and onboard new tools to the MCP gateway
Extend the corporate chatbot with new self-service automations and knowledge sources
Connect AI solutions to enterprise systems, including ITSM/Jira, ServiceNow-style workflows, SaaS apps, AD/Entra ID and REST APIs
Track and report AI usage, cost and KPIs, such as ticket deflection and automation runs
Apply security and governance, including authentication, least-privilege access, data protection and audit/SOX requirements
Run enablement work through documentation, user guides, live sessions/workshops and Tier-3 support for AI tools
Evaluate new AI technologies and vendors, and build proofs of concept
Take AI use cases from idea to production and identify automation opportunities with business and IT stakeholders

Requirements

What you’ll need

3+ years of hands-on experience in DevOps, automation, systems engineering or software development
Strong scripting/programming skills
Hands-on experience with LLMs / GenAI: prompt engineering, RAG, agents, function/tool calling
Experience with REST APIs, JSON, webhooks and integrating SaaS/enterprise systems
Working knowledge of Docker / Kubernetes, CI/CD and Git
Strong communication skills; able to work with non-technical stakeholders and explain AI clearly
Fluent Hebrew and English
Nice to have: Experience with MCP (Model Context Protocol) servers/clients
Nice to have: Familiarity with identity & access (Entra ID/AD, OAuth, SSO) and security best practices
Nice to have: Solid troubleshooting skills in Linux and Windows environments
Nice to have: Experience with AI platforms such as Amazon Quick / Bedrock, Azure OpenAI, Copilot Studio, Open WebUI, or LangChain/LangGraph
Nice to have: Background in IT operations / ITSM (Jira Service Management)
Nice to have: Experience with Azure (Key Vault, App Services) or AWS
Nice to have: Experience with cost monitoring/observability for AI workloads
Nice to have: Experience running technical training or workshops