AI & Automation Architect – Enterprise AI, Automation & Autonomous Operations

AI & Automation Architect – Enterprise AI, Automation & Autonomous Operations
Location: Noida
About the Role
We are seeking an AI & Automation Architect to drive end-to-end architecture across AI, GenAI, LLMs, Agentic AI, Automation, AIOps, Cloud, Security, and Enterprise Infrastructure. The role is responsible for taking ideas from business problem identification through architecture, implementation, production deployment, and operational adoption.The successful candidate will define enterprise AI architecture, establish governance and security standards, design scalable AI-native platforms, and collaborate across Infrastructure, Network, Security, Workplace, Service Management, and Hybrid Cloud domains.
Key Responsibilities
Own and drive enterprise AI and automation architecture, standards, and roadmap.
Translate business needs into AI, GenAI, Agentic AI, AIOps, and automation solutions.
Lead architecture from discovery and design through production deployment and adoption.
Define reusable architecture patterns, governance, and best practices.
Provide technical leadership through prototyping, design reviews, and engineering guidance.
Design and govern LLM, GenAI, RAG, and Agentic AI architectures.
Architect Microsoft Copilot, Copilot Studio, Microsoft Foundry, and Azure OpenAI solutions.
Design single-agent and multi-agent systems with secure tool integration and orchestration.
Build enterprise knowledge architectures using RAG, vector databases, embeddings, and knowledge graphs.
Define AIOps, observability, and intelligent operations frameworks.
Establish NRE, SRE, PRE, and MIRE reliability engineering practices.
Drive automation using Ansible, Python, PowerShell, Bash, Terraform/OpenTofu, and APIs.
Implement Infrastructure-as-Code, GitOps, and policy-driven automation standards.
Define AI security, Zero Trust, governance, and compliance controls.
Establish LLMOps, MLOps, and GenAIOps processes for lifecycle management and monitoring.
Collaborate across Infrastructure, Network, Security, Workplace, Service Management, and Cloud teams.
Ensure scalable, secure, resilient, and operationally efficient AI-native platforms.
Experience Required
✔ 15+ years of experience in Enterprise Architecture, Infrastructure, Cloud, Automation, Software Engineering, or related technology domains
✔ Proven experience delivering Enterprise AI/GenAI and Automation Platforms
✔ Strong knowledge of Network, Security, Data Center, Workplace, and Cloud Operations
✔ Experience leading initiatives from business case and architecture through production rollout and adoption
✔ Strong stakeholder management and architecture governance capabilities
Primary Skills
AI & GenAI
• GenAI
• LLMs / SLMs
• Multimodal AI
• Foundation Models
• Fine-Tuning
• LoRA / PEFT
• Quantization
• Distillation
• Agentic AI
• MCP
• A2A
Knowledge & Retrieval
• Enterprise RAG
• Agentic RAG
• Embeddings
• Vector Databases
• Knowledge Graphs
• Semantic Search
• Hybrid Search
• Context Engineering
Microsoft AI Ecosystem
• Microsoft Copilot
• Copilot Studio
• Microsoft Foundry
• Azure OpenAI
• Power Platform
• Power Automate
• Azure Functions
• Logic Apps
• API Management
Automation & Platform Engineering
• Ansible Automation Platform
• Python
• PowerShell
• Bash
• Terraform / OpenTofu
• REST APIs
• Git
• GitOps
• CI/CD
Operations & Reliability
• AIOps
• Observability
• OpenTelemetry
• NRE
• SRE
• PRE
• MIRE
• SLI / SLO
• Error Budgets
Security & Governance
• Zero Trust
• AI Security
• RBAC
• PAM
• DLP
• LLMOps
• MLOps
• GenAIOps
• AI Governance
• Compliance & Risk Management
Preferred Certifications
Microsoft Azure Architect
Microsoft AI Engineer
Microsoft DevOps
Microsoft Security
AI/ML Certifications
GenAI Certifications
Terraform Certification
Red Hat Ansible Automation Certification
VMware Certifications
Aruba Certifications
Palo Alto Certifications
TOGAF or equivalent Enterprise Architecture Certification
ITIL Certification
ServiceNow Certification
SRE Certification
Cloud Architecture Certifications

Work arrangement
Hybrid