AI DevOps Engineer

Location: Atlanta, GA (Hybrid – 3 days onsite)

Position Overview

We are seeking a highly experienced AI DevOps Engineer to support the design, implementation, and optimization of enterprise AI platforms and cloud infrastructure. This role will focus on cloud architecture, Infrastructure as Code (IaC), DevSecOps, AI/ML operations, observability, security, governance, and Agentic AI systems.

The ideal candidate will have extensive experience building scalable cloud environments, implementing DevOps best practices, and enabling production-grade AI solutions in regulated enterprise environments.

Main Skills Required

• Cloud Platforms: Google Cloud Platform (preferred), Azure, Databricks
• Infrastructure as Code (IaC): Terraform, Bicep
• DevSecOps: CI/CD pipelines, IAM, encryption, secrets management
• AI/ML Operations: Model monitoring, drift detection, retraining strategies
• Observability: Logging, alerting, monitoring frameworks
• AI Governance: Compliance, model risk management, auditability
• FinOps: Cloud cost optimization and resource utilization
• Agentic AI: LangChain, AI agents, orchestration frameworks
• Programming & Automation: Scripting and cloud automation tools

Key Responsibilities

• Design, deploy, and maintain enterprise cloud infrastructure supporting AI/ML workloads.
• Implement Infrastructure as Code (IaC) using Terraform, Bicep, or similar automation tools.
• Develop and manage secure CI/CD pipelines with integrated governance and compliance controls.
• Architect scalable, highly available AI platforms across cloud environments.
• Implement AI observability frameworks covering model performance, drift detection, reliability, and business KPIs.
• Support AI/ML lifecycle management, including monitoring, retraining, logging, alerting, and incident response.
• Embed security, compliance, and model risk management controls into AI development and deployment processes.
• Drive FinOps practices, including cloud cost optimization and enterprise cost visibility.
• Design and operationalize Agentic AI solutions, including orchestration, testing, monitoring, and governance.
• Establish best practices for AgentOps, AI platform reliability, and governance.

Required Qualifications

• 10+ years of experience in cloud architecture, automation, and DevOps engineering.
• Strong hands-on experience with Google Cloud Platform (preferred), Azure, or Databricks.
• Expertise in Terraform, Bicep, or other IaC tools.
• Proven experience implementing secure CI/CD pipelines and DevSecOps practices.
• Hands-on experience supporting production AI/ML environments, including monitoring and drift detection.
• Strong knowledge of IAM, encryption, secrets management, and cloud security controls.
• Experience with AI observability, logging, alerting, and centralized monitoring frameworks.
• Familiarity with LLM-based applications, AI agents, prompt engineering, and LangChain.
• Experience designing AI systems for regulated enterprise environments.

Preferred Qualifications

• Experience implementing multi-cloud AI infrastructure with governance and policy controls.
• Knowledge of AI FinOps, including token optimization and cost-performance tradeoffs.
• Experience with model risk management, explainability, and access governance.
• Understanding of autonomous AI system failure modes and mitigation strategies.
• Experience supporting agent-based systems at scale, including multi-agent coordination and state management.