AI & Automation Architect

RDT is looking for an AI & Automation Architect to lead the architecture and delivery of enterprise-scale AI, automation and intelligent operations initiatives. This is a hands-on architecture role covering the journey from business need and architecture through POC, production deployment and operational adoption. You will define target architectures, standards and reusable patterns across AI/GenAI, automation, AIOps, cloud, infrastructure, security and enterprise platforms. Key responsibilities

• Define enterprise AI and automation architectures, standards, patterns and technology roadmaps.
• Lead solutions from discovery and business case through POC, production deployment and lifecycle management.
• Design and evaluate solutions using LLMs, SLMs, RAG, Agentic RAG, embeddings, vector/semantic search, knowledge graphs and AI agents.
• Architect agentic solutions using tool calling, MCP, A2A and enterprise integrations.
• Work with Microsoft Copilot, Copilot Studio, Azure OpenAI, Microsoft Foundry, Power Platform, Azure Functions, Logic Apps and API Management.
• Design automation and intelligent operations using Ansible, Python, PowerShell, Bash, Terraform/OpenTofu, APIs, Git/GitOps and CI/CD.
• Apply AI and automation across Data Center, Network, Security, Workplace/EUC, Service Management and Hybrid Cloud environments.
• Architect AIOps/SRE and autonomous remediation patterns using observability, telemetry, event correlation and OpenTelemetry.
• Establish secure AI architectures covering Zero Trust, RBAC, data protection, guardrails, approvals, auditability and governance.
• Define LLMOps/MLOps/GenAIOps practices for testing, evaluation, monitoring, versioning, quality and cost management.
• Collaborate with infrastructure, security, network, workplace, cloud and service-management teams and translate business requirements into scalable technical solutions.
• Guide technical teams through architecture reviews, prototyping, implementation and production adoption.

Key technical areas

• AI/GenAI: LLMs, SLMs, multimodal AI, foundation models, fine-tuning, RAG, Agentic RAG, embeddings, vector databases, semantic search, knowledge graphs, AI agents, MCP, A2A and AI evaluation.
• Microsoft AI: Copilot, Copilot Studio, Azure OpenAI, Microsoft Foundry, Power Platform, Azure Functions, Logic Apps, API Management.
• Automation & DevOps: Ansible, Python, PowerShell, Bash, Terraform/OpenTofu, REST APIs, Git, GitOps and CI/CD.
• Infrastructure: VMware, Hyper-V, Azure Local/Azure Stack HCI, Windows/Linux, Active Directory, storage, backup, disaster recovery and HCI.
• Network & Security: Aruba, Palo Alto, SD-WAN, VXLAN/EVPN, Zero Trust, NAC, SASE/SSE, SIEM, SOAR and NDR.
• Workplace/EUC: Microsoft 365, Intune, Autopilot, Entra ID, Defender, Citrix and Digital Employee Experience.
• Operations: SRE/PRE/MIRE, SLI/SLO, observability, error budgets, autonomous remediation, AIOps and event management.
• Service Management: ServiceNow ITSM/ITOM/CMDB, AIOps, monitoring and Power BI.
• Governance: AI security, responsible AI, data protection, RBAC, guardrails, auditability, approval workflows and FinOps.

Required experience

• 15+ years of experience across enterprise architecture, infrastructure, cloud, automation and/or software engineering.
• Strong hands-on experience designing and delivering enterprise AI/GenAI and automation solutions beyond POCs.
• Broad understanding of enterprise infrastructure across cloud, data center, networking, security, workplace and service management.
• Proven experience taking solutions from business requirement → architecture → POC → production → adoption.
• Strong experience with LLM/GenAI architecture, RAG, AI agents and enterprise AI integrations.
• Strong experience with Python and/or PowerShell, APIs and infrastructure automation.
• Experience with Ansible and Terraform/OpenTofu and modern Git/CI/CD practices.
• Experience with Microsoft AI platforms such as Copilot, Copilot Studio, Azure OpenAI and/or Microsoft Foundry.
• Strong understanding of security, Zero Trust, governance, identity and data protection in enterprise AI environments.
• Experience with AIOps, SRE/observability and intelligent automation.
• Strong architecture communication skills, with the ability to work across technical teams and business stakeholders.
• Bachelor's degree or equivalent professional experience.

Preferred

• Azure Architect, Azure AI Engineer, Azure DevOps or Azure Security certifications.
• AI/ML/GenAI or cloud AI certifications.
• Terraform or Ansible certifications.
• VMware, Aruba or Palo Alto certifications.
• TOGAF or similar enterprise architecture framework.
• ITIL and/or ServiceNow experience.
• SRE, cloud architecture or AI governance experience.