# Enterprise AI Platform Lead

**Company:** [RSA](https://hotfix.jobs/companies/rsa)
**Location:** Cairo, Egypt
**Role:** AI Research
**Experience:** 7+ years
**Skills:** Microsoft Copilot, Copilot Studio, Azure Ai Foundry, Azure Openai, Anthropic Claude, LLMs, AI Agents, Prompt Engineering, RAG, Model Context Protocol, Microsoft Azure, Kubernetes, Docker, Terraform, Python
**Posted:** 2026-08-12

> Leads the strategy, architecture, governance, operations, and adoption of an enterprise AI platform. The role builds AI agents and integrations, manages model and platform lifecycle, and ensures secure, compliant, scalable, and cost-effective AI delivery.

## Job Description

## Responsibilities
- Own the enterprise AI platform ecosystem, including strategy, roadmap, architecture standards, governance, operational standards, lifecycle management, and adoption enablement.
- Drive enterprise-wide AI adoption while ensuring security, reliability, scalability, and compliance.
- Design, implement, support, and troubleshoot enterprise AI solutions, including:
  - AI agents and copilots
  - Retrieval-Augmented Generation (RAG) architectures
  - Enterprise AI integrations
  - Multi-agent solutions
  - AI orchestration patterns
  - Integrations with enterprise applications
  - Reusable AI services and frameworks
- Manage the complete lifecycle of enterprise AI agents and establish standards for development, testing, security reviews, approvals, production deployment, change management, and retirement.
- Define governance controls for agent ownership, prompt management, knowledge sources, connector usage, model selection, and version control.
- Manage enterprise use of AI models across multiple platforms, including Azure OpenAI, Claude, Codex, and other approved providers.
- Define model approval policies, usage guidelines, selection criteria, and performance standards.
- Optimize AI response quality, cost efficiency, model performance, scalability, and user experience.
- Own AI platform financial governance, including consumption monitoring, budget forecasting, license optimization, credit and token management, and cost allocation.
- Implement quotas, budget controls, consumption policies, chargeback/showback, and cost-optimization frameworks.
- Investigate cost anomalies, token spikes, excessive model consumption, and resource waste.
- Partner with Security, Privacy, Risk, Compliance, and Legal teams to establish AI controls, including DLP, RBAC, environment segregation, data classification, audit, and monitoring.
- Design integration architectures between AI platforms and enterprise applications such as Salesforce, NetSuite, Jira, SharePoint, Microsoft 365, Dataverse, ERP platforms, knowledge management systems, and internal APIs.
- Define connectivity standards and manage MCP implementations, API integrations, agent-to-system communication, external AI services, and enterprise tool connectivity.
- Establish monitoring and observability for AI agents, platform health, model utilization, system performance, security events, usage trends, and user adoption.
- Develop runbooks, incident response procedures, support processes, and escalation workflows.
- Lead troubleshooting of agent failures, integration issues, model outages, performance degradation, and cost anomalies.
- Advise teams on AI use cases, platform standards, best practices, templates, and controlled self-service development.
- Balance innovation with governance and operational excellence.

## Requirements
- Bachelor's degree in Computer Science, Information Technology, Engineering, or Information Systems.
- 7–10+ years of experience in enterprise technology, infrastructure, cloud engineering, platform engineering, or solution architecture.
- 3+ years of experience implementing or managing AI, GenAI, or large language model platforms.
- Experience designing and operating enterprise SaaS platforms.
- Experience leading technical initiatives across multiple teams.
- Experience working in regulated enterprise environments.

## Skills and Technologies
- Microsoft Copilot and Copilot Studio
- Azure AI Foundry
- Azure OpenAI
- Anthropic Claude
- Codex
- Large Language Models (LLMs)
- Agentic AI and AI agents
- Prompt engineering
- Retrieval-Augmented Generation (RAG)
- Model evaluation
- AI governance
- Model Context Protocol (MCP)
- Microsoft Azure
- AWS
- Kubernetes
- Docker
- Terraform
- Infrastructure as Code (IaC)
- Microsoft Entra ID
- OAuth and SAML
- Role-Based Access Control (RBAC)
- Conditional Access
- Enterprise security architecture
- Python
- PowerShell
- REST APIs
- GitHub
- Azure DevOps
- CI/CD pipelines
- Power Platform

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**Canonical:** https://hotfix.jobs/jobs/c6299e03-ccfd-4dcd-acb2-71a8f409293c