AI Ops Lead / AIOps Technical Delivery Lead

About the Role

Seeking an AI Ops Lead / AIOps Technical Delivery Lead to serve as the primary technical delivery lead for enterprise-wide AIOps and automation initiatives. This role focuses on Agentic AI, AIOps, observability, automation, and cloud infrastructure within a global enterprise IT environment.

Required Experience

• 8+ years of experience leading complex technical projects, product delivery, and cloud infrastructure rollouts
• Experience working within a global enterprise IT environment
• 2+ years of experience leading AI/AIOps platform deployments
• Strong experience with enterprise-scale automation and cloud initiatives
• Experience working with global delivery models and cross-functional technical teams

AI & Agentic AI Skills

• Deep understanding of AI concepts including Large Language Models (LLMs), Agentic AI, multi-agent reasoning, tool-calling architectures, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP)
• Experience designing or implementing Agentic AI architectures
• Experience deploying LLM-based solutions in production environments
• Experience with Google Cloud Vertex AI
• Experience with agentic AI frameworks and dynamic agent registries
• Strong understanding of AI tool-calling interfaces and integrations
• Ability to translate complex enterprise environments into contextual schemas for AI consumption

Cloud & Observability Skills

• Hands-on experience with enterprise observability and monitoring platforms such as Dynatrace, Splunk, and CloudWatch
• Strong experience with cloud environments, particularly Google Cloud Platform (GCP) and AWS
• Experience with hybrid and multi-cloud environments
• Knowledge of GCVE and hybrid cloud environments
• Experience with telemetry ingestion and monitoring standardization
• Experience implementing automated alerting and self-healing workflows

DevOps / SRE / Automation

• Strong understanding of Site Reliability Engineering (SRE) principles
• Experience with automated testing
• Infrastructure as Code (IaC) experience
• Strong experience with Ansible, Terraform, PowerShell, and Shell scripting
• Experience with CI/CD pipeline automation
• Experience overseeing data pipelines and ETL validation
• Familiarity with Snowflake and enterprise data validation processes
• Experience developing automated remediation and self-healing solutions

Key Responsibilities

• Serve as the primary technical delivery lead for enterprise-wide AIOps and automation initiatives
• Orchestrate Agentic AI and AIOps platform deployments
• Drive milestone tracking, code integration, testing, and production deployment
• Coordinate deployment of multi-agent reasoning systems, dynamic agent registries, tool-calling interfaces, and agentic AI frameworks
• Utilize Google Cloud Vertex AI, MCP, and related agentic technologies
• Lead enterprise observability and self-healing automation programs
• Oversee telemetry ingestion and monitoring standardization across multi-cloud infrastructure
• Drive automated alerting and self-healing workflows
• Develop and deploy vulnerability tracking workflows
• Establish automated security remediation frameworks across application and infrastructure portfolios
• Ensure compliance with enterprise security and governance standards
• Coordinate engineering, application support, data, and security teams
• Manage resource dependencies and competing priorities
• Drive accountability across multiple technical teams
• Track project milestones, delivery health, and operational improvements
• Establish KPIs covering delivery health, token consumption, operational MTTR improvements, and financial savings
• Build executive reporting frameworks to measure the business value and cost savings of AI and automation initiatives
• Provide concise status updates to executive leadership
• Anticipate technical bottlenecks and independently drive resolution
• Translate complex technical information into clear executive-level communication

Governance & Security

• Establish appropriate guardrails for data security, AI safety, regulatory compliance, and enterprise governance
• Ensure AI and automation solutions follow organizational security standards
• Develop governance practices for enterprise AI/AIOps deployments
• Support vulnerability management and automated remediation initiatives

Leadership & Managerial Skills

• Ability to work directly with clients in an onsite environment
• Strong client engagement and stakeholder management skills
• Proven technical leadership abilities
• Experience managing global delivery teams
• Strong decision-making and problem-solving skills
• Excellent communication and executive presence
• Ability to manage complex, high-visibility programs
• Strong thought leadership capabilities
• Experience with reporting, governance, and executive communications
• Ability to operate with a high degree of autonomy

Pre-Screening Questions

• Explain an Agentic AI architecture you have designed or implemented. What problem did it solve?
• What is the difference between traditional AI workflows and Agentic AI systems?
• How have you used LLMs in production environments?
• What is RAG (Retrieval-Augmented Generation), and where have you applied it?
• What experience do you have with MCP (Model Context Protocol) or tool-calling architectures?
• Describe your experience with Google Cloud Vertex AI
• How have you implemented AIOps or automated self-healing solutions?
• Describe your experience with enterprise observability platforms such as Dynatrace, Splunk, or CloudWatch
• How have you used Ansible and Terraform in enterprise automation?
• Describe an automation initiative where you achieved measurable operational or financial savings