Enterprise AI Platform Lead
RSA Security, LLC10 hours ago
Cairo, EgyptStaff+
Responsibilities
- Own the enterprise AI platform strategy, roadmap, architecture standards, governance framework, operational standards, and lifecycle management.
- Lead the design, implementation, troubleshooting, architecture review, and support of enterprise AI solutions.
- Build AI agents and copilots, RAG architectures, multi-agent solutions, AI orchestration patterns, enterprise integrations, and reusable AI services and frameworks.
- Establish standards and governance controls for agent development, testing, security review, approval, deployment, change management, retirement, prompts, knowledge sources, connectors, model selection, and version control.
- Manage enterprise AI model usage across Azure OpenAI, Claude, Codex, and other approved providers, including model policies and performance standards.
- Own AI platform financial governance, including consumption monitoring, forecasting, license and credit optimization, token management, cost allocation, quotas, chargeback, showback, and anomaly investigation.
- Partner with Security, Privacy, Risk, Compliance, and Legal teams to implement AI governance, DLP, RBAC, environment segregation, data classification, audit, monitoring, and responsible AI controls.
- Design secure integration architectures between AI platforms and Salesforce, NetSuite, Jira, SharePoint, Microsoft 365, Dataverse, ERP platforms, knowledge systems, internal APIs, and business services.
- Design and manage MCP implementations, API integrations, agent-to-system communication, external AI service integrations, and enterprise tool connectivity.
- Establish monitoring, observability, runbooks, incident response, support, escalation, and troubleshooting processes for agents, platforms, models, integrations, security events, usage, and costs.
- Advise business and technical teams on AI use cases, platform standards, best practices, templates, education, and controlled self-service development.
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.
- Experience with Microsoft Copilot, Copilot Studio, Azure AI Foundry, Azure OpenAI, Anthropic Claude, Codex, and enterprise AI platforms.
- Knowledge of LLMs, agentic AI, AI agents, prompt engineering, RAG, model evaluation, AI governance, and MCP.
- Experience with Microsoft Azure, Kubernetes, Docker, Terraform, platform engineering, and infrastructure as code; AWS is preferred.
- Experience with Microsoft Entra ID, OAuth, SAML, RBAC, Conditional Access, and enterprise security architecture.
- Experience with Python, PowerShell, REST APIs, GitHub, Azure DevOps, CI/CD pipelines, and Power Platform.
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