Principal AIOps Architect - Cloud & Agentic AI

We are looking for a Principal AIOps Architect to spearhead large-scale AIOps, Intelligent Operations, and Agentic AI transformation efforts, guiding architectural direction for cloud, automation, and AI-powered operational intelligence platforms within major enterprise programs. Responsibilities Direct enterprise-scale AIOps, Intelligent Operations, Agentic AI, and automation transformation initiatives by establishing target-state architecture, modernization roadmaps, governance frameworks, and reusable solution patterns Design observability and operational intelligence solutions spanning metrics, logs, traces, events, topology, service dependencies, incidents, deployments, and configuration changes to support anomaly detection, event correlation, service-impact analysis, and AI-assisted root cause analysis Build Agentic AI solutions for IT Operations leveraging Amazon Bedrock/AgentCore, Microsoft Foundry/Azure OpenAI, or Gemini/Vertex AI Agent Engine to support reasoning, knowledge retrieval, tool invocation, multi-step investigation, recommendations, and operational decision-making Develop autonomous and semi-autonomous remediation solutions incorporating policy controls, identity and access verification, risk assessment, Human-in-the-Loop approvals, rollback capability, recovery validation, auditability, and feedback loops Connect AIOps platforms with ITSM/CMDB, observability tools, CI/CD pipelines, cloud-management systems, knowledge bases, security platforms, automation tools, and enterprise APIs, including ServiceNow or similar solutions Oversee enterprise architecture reviews, solution assurance, design authority decisions, non-functional requirements, security, resilience, scalability, operational governance, and technical leadership spanning Cloud, SRE, DevOps, Platform, Operations, and AI teams Drive RFP/RFI/RFQ processes and pre-sales solutioning, encompassing technical discovery, solution architecture, transformation strategy, estimations, staffing models, implementation roadmaps, assumptions, risks, dependencies, TCO analysis, and proposal development Partner with senior customer and executive stakeholders, lead architecture workshops and solution defenses, and work alongside Sales, Pre-Sales, Delivery, Engineering, Practice, and Commercial teams to craft technically sound and competitive solutions Requirements 18-25 years of overall IT experience, with substantial background in Enterprise/Solution Architecture, Cloud, SRE, DevOps, Platform Engineering, IT Operations, Automation, or AIOps Deep experience building large-scale AIOps and intelligent operations platforms, covering observability, anomaly detection, event correlation, noise reduction, service-impact analysis, AI-assisted RCA, remediation, and operational automation Mastery of at least one major cloud platform—AWS, Microsoft Azure, or Google Cloud—including enterprise cloud architecture, security, identity, networking, governance, resilience, and scalability Practical architecture experience with at least one Agentic AI ecosystem, such as Amazon Bedrock/AgentCore, Microsoft Foundry/Azure OpenAI, or Gemini/Vertex AI Agent Engine/Google ADK Solid grasp of Agentic AI architectures, including reasoning, planning, tool/function calling, RAG/knowledge grounding, context and memory management, multi-agent orchestration, agent evaluation, Human-in-the-Loop processes, guardrails, and policy enforcement Background in designing autonomous/self-healing operations, event-driven remediation, workflow orchestration, ITSM integration, operational governance, and secure interactions between AI agents and enterprise systems Strong Python skills for building Agentic AI solutions, APIs, integrations, automation, telemetry processing, orchestration, and rapid prototyping Track record in RFP/RFI solutioning, pre-sales architecture, technical proposals, estimations, solution defense, executive stakeholder engagement, and technical leadership across large enterprise transformation programs Nice to have Experience with multiple major cloud platforms and familiarity with enterprise observability tools such as Splunk, Dynatrace, Datadog, Grafana, Prometheus, or Elastic Knowledge of LangGraph, Semantic Kernel, Strands Agents, Google ADK, MCP, A2A, RAG, vector databases, or knowledge graphs Background in SRE, FinOps, cloud economics, capacity optimization, predictive operations, and managed-services solutioning Relevant certifications in Cloud Architecture, AI, Enterprise Architecture, SRE, ITIL, or TOGAF