Required AI Implementer
About the team:
The IT AI team is responsible for rolling out enterprise AI tools for development and productivity across; including AI coding assistants, enterprise copilots and agents. The team builds and runs AI solutions that turn business needs into practical, secure and reliable tools.
We're looking for a hands-on AI Implementer to take AI use cases from idea to production. You'll work with business and IT stakeholders to find automation opportunities. You'll then build agents, MCP integrations and workflows, and make sure they run securely and reliably and are actually used.
What will your job look like:
Lead the company-wide rollout of development and productivity tools (e.g., 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 the different business units.
Develop and maintain MCP server integrations (e.g., Jira, Confluence, SharePoint, Jenkins, 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 (ITSM/Jira, ServiceNow-style workflows, SaaS apps, AD/Entra ID, REST APIs).
Track and report AI usage, cost and KPIs, such as ticket deflection and automation runs.
Apply security and governance: authentication (OAuth/tokens), least-privilege access, data protection, and audit/SOX requirements.
Run enablement work: documentation, user guides, live sessions/workshops, and Tier-3 support for AI tools.
Evaluate new AI technologies and vendors, and build PoCs.
Requirements: 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.
Familiarity with identity & access (Entra ID/AD, OAuth, SSO) and security best practices.
Experience with AI platforms such as Amazon Quick / Bedrock, Azure OpenAI, Copilot Studio, Open WebUI, or LangChain/LangGraph.
This position is open to all candidates.