Ragavendren Chandrasekaran
Agentic AI • AIOps • Intelligent Automation
Enterprise AI Architect
I build enterprise AI systems that work — not proofs of concept. Leveraging 18 years of experience in IT Infrastructure & Automation, alongside deep expertise in Agentic AI and AIOps, I design self-healing infrastructure where AI agents plan, reason, and act across enterprise environments without human intervention. My speciality is fine-tuning Small Language Models (SLMs) on proprietary IT data — delivering GPT-grade intelligence at a fraction of the cost, fully on-premise, and within Zero-Trust security boundaries. I have operationalised AI at scale across global organisations — turning automation from a project into a repeatable, governed enterprise capability that measurably reduces cost, risk, and operational toil.
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Estimate 3-year ROI when migrating from commercial APIs (GPT-4) to fine-tuned local SLMs.
Simulate how fine-tuned SLM agents intercept infrastructure alerts, coordinate recovery playbooks, apply zero-trust checks, and run self-healing steps.
Hover over each orchestration stage to examine security guardrails, validation checks, and execution policies.
Program Leader – Enterprise AI, AIOps & Intelligent Automation Solutions
• Lead Enterprise AI and Intelligent Automation initiatives within IT, focusing on building scalable, governed AI capabilities embedded into real operational workflows.
• Architect and develop cost-effective Small Language Models (SLMs) for Infrastructure teams to automate incident remediation, monitoring, and system administration.
• Design Agentic AI systems that plan, reason, and execute tasks across enterprise systems with built-in security, control, and auditability.
• Implement AIOps and self-healing operations that integrate observability, workflow processes, and execution to improve infrastructure resilience.
• Outcome-driven approach: turning AI into a repeatable enterprise capability, helping the organization operate smarter, faster, and with greater confidence at scale.
Senior Manager – Modern Workplace Services
• Managed and developed Modern Workplace solutions for 300K+ endpoints across a global scale covering Intune, M365, AVD, Tanium, and Nexthink.
• Generative AI & Agentic AI: Enabled proactive IT support and self-healing diagnostics with AI Agents, ML-based analytics, and context-aware recommendations.
• Solution Architecture & Automation: Streamlined endpoint operations, service delivery, and SCCM-to-Intune migration using custom PowerShell automation.
• Transformation & Zero-Trust: Architected secure, Zero-Trust endpoints, digital onboarding workflows, and defined a 3-year EUC modernization roadmap.
• Mentored cross-functional teams to drive innovation and operational excellence across modern workplace services.
Consultant – End User Computing
• Delivered MECM/Intune engineering and operations for enterprise clients across global environments.
• Enhanced application delivery and endpoint performance through custom PowerShell automation.
• Produced advanced SQL-driven reports with infographic insights for strategic planning and capacity management.
• Designed and implemented modern device management for Windows 10 at scale.
• Served as a trusted SME, advising clients on SCCM/Intune transformation, latency, and compatibility considerations.
Technical Lead – SCCM Architect
• Designed and supported SCCM, WSUS, and Active Directory for 15K+ endpoints distributed globally.
• Planned and executed enterprise Windows XP/7/10 migrations for 10K+ devices using SCCM, MDT, AIK, and PowerShell scripting.
• Delivered SCCM site migrations (OS, hardware, service packs) with zero downtime across business-critical environments.
• Implemented secure cloud infrastructure to support remote workforce during enterprise expansion.
• Developed POC labs for client demos, and implemented Intune cloud workspace, Exchange, and SharePoint infrastructure.
• Established role-based SCCM security matrices (L1–L4) ensuring compliance, governance, and controlled access.
Technical Analyst – Desktop Engineering Group | Jun 2007 – Sep 2009
• Supported 80K endpoints across 67 countries using SCCM and WSUS for enterprise patching and compliance.
• Developed automation utilities using WMI, VBScript, and .NET to enhance SCCM/WSUS operations.
• Automated client management and optimized SCCM collections for large-scale efficiency.
• Delivered SQL-based reports on patch compliance and endpoint health.
• Provided Level 3 support for SCCM/WSUS/AD GPO issues, stabilizing patch and compliance operations.
I have done my Master of Business Administration specialized in Information Technology with Distinction from United Business Institutes, Brussels. (Recognized by Middlesex University, London)
Completed the Microsoft Certfications to achieve - Microsoft Certified Solutions Associate in Windows 10
- Installing and Configuring Windows 10
- Configuring Windows Devices
Completed the Microsoft Certfications to achieve - Microsoft Certified Solutions Expert in Mobilty
- Administering System Center Configuration Manager and Intune
Completed the Microsoft Architecting Microsoft Azure Solutions
Completed my first SCCM 2007 Certification in first attempt.
MCTS: - Microsoft Certified Technical Specialist (SCCM 2007)
I did completed my first Microsoft Professional Certification in Windows XP in first attempt.
MCP: - Microsoft Certified Professional (Windows XP)
A comprehensive technical guide to Parameter-Efficient Fine-Tuning (PEFT) methodologies for enterprise Small Language Models (SLMs). Compare LoRA, Prefix Tuning, and Prompt Tuning.
A deep-dive technical article on Low-Rank Adaptation (LoRA) mechanics, covering weight matrices decomposition, rank r, scaling factor alpha, and QLoRA.
A technical guide on aligning domain-specific SLMs using Direct Preference Optimization (DPO) and Reinforcement Learning to prevent hallucinations and ensure Zero-Trust execution.
A technical guide on model quantization and compiling 8B Small Language Models (SLMs) for local edge execution using GGUF, AWQ, and GPTQ.
An in-depth technical analysis comparing Retrieval-Augmented Generation (RAG) and Fine-Tuning, designing hybrid Retrieval-in-the-Loop (RIL) architectures for SLMs.
A deep-dive technical article on building self-healing IT infrastructure by deploying preference-aligned, quantized SLM agents at the edge.
I respond within 24 hours — reach out via any channel below.
Chennai, India — Available for remote & global engagements
