AI Ops Lead / AIOps Technical Delivery Lead

Job Description – AI Ops Lead

• Job Title: AI Ops Lead / AIOps Technical Delivery Lead
• Location: Louisville, KY
• Duration: 6 months
• Experience Required: 8–10 years
• Primary Skills: AIOps, AI/ML, GCP, Automation, Ansible, Terraform
• Role Focus: Agentic AI, AIOps, Observability, Automation, Cloud Infrastructure

Education

• Master’s degree preferred.
• Bachelor’s degree required in:
  • Computer Science
  • Information Technology
  • Systems Engineering
  • Related technical field

Required Experience

• 8+ years of experience leading complex:
  • Technical projects
  • Product delivery
  • 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)
  • 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
  • CloudWatch
• Strong experience with cloud environments, particularly:
  • Google Cloud Platform (GCP)
  • 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
  • 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
  • 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
  • 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
  • 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.

Key Resume Search Keywords

• GCP
• AIOps
• AI/ML
• Agentic AI
• LLM
• RAG
• MCP
• Automation
• GCVE
• Hybrid Cloud
• AWS
• Vertex AI
• Dynatrace
• Splunk
• CloudWatch
• Ansible
• Terraform
• PowerShell
• Shell Scripting
• SRE
• DevOps
• Observability
• Self-Healing Automation

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.

Role Classification

• Role Description: AI Ops Lead
• Essential Skills: AI Ops Lead
• Desirable Skills: Ansible, Terraform
• Keyword: AIOps / AI Automation
• Skills: Digital – Ansible | Digital – Terraform
• Experience Required: 8–10 years