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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Manager, AI & Agentic Engineering - AIOps/LLMOps Engineer - **Company:** Avanade Inc. - **Location:** Atlanta, GA, United States - **Experience:** Experienced - **Salary:** $96,000 - $156,730 - **Contract:** Permanent contract - **Skills:** AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Application Performance Management, Audit Trail, Automation of Tests, Microsoft Azure, Bash Shell, C Sharp (Programming Language), Cloud Computing, Cloud Computing Security, Cloud Engineering, Continuous Integration, DevOps, Github, HP Systems Insight Manager, Python (Programming Language), Machine Learning, Windows PowerShell, Reliability Engineering, Azure Machine Learning, Runbook, Software Engineering, Systems Integration, TypeScript, Management of Software Versions, Cloud Platform System, Cloud Monitoring, Generative AI, Agentic-AI, Git, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Bicep, Azure AKS, Machine Learning Operations, Terraform, AIOps, Azure Resource Manager, Docker, Container Apps - **Published:** November 13, 2026 - **Apply:** https://www.careerbuilder.com/job-details/associate-manager-ai-agentic-engineering-aiops-llmops-engineer-atlanta-ga--f1b5dd10-1d50-4faa-8b58-67082d984a3a ## About the Role Artificial Intelligence (AI), Automation, Prototyping, Microsoft Windows Azure, Artificial Intelligence (AI), Cloud Computing, Reliability Engineering, QoS (Quality of Service), Data Modeling, Machine Learning, * Minimum of 3+ years of experience in AI, Data, cloud engineering, platform engineering, DevOps, MLOps, or consulting roles. * Minimum of 2+ years of hands-on experience deploying or operating AI/ML or generative AI solutions using Microsoft Foundry/Azure AI Foundry, Azure Machine Learning, or comparable platforms. * Strong software development and automation skills in Python, PowerShell, Bash, C#, TypeScript, or a comparable language. * Practical experience with DevOps, MLOps, site reliability engineering, cloud operations, or production application support. * Working knowledge of AI lifecycle practices, including CI/CD, versioning, evaluation, observability, reliability, cost management, responsible AI, and incident response. * Experience with Azure cloud services, APIs, Git, automated testing, infrastructure as code, application monitoring, identity, and secure cloud development. About you Professional Skills * Highly organized with strong problem-solving and analytical capabilities * Ability to collaborate effectively across diverse, matrixed teams and global environments * Strong communication and interpersonal skills with the ability to build trust and credibility with stakeholders * Demonstrated ability to operate both strategically and tactically, balancing big-picture thinking with technical execution * Commitment to innovation, continuous learning, and delivering high-quality client outcomes Preferred Qualifications * Microsoft certification in Azure AI, Azure DevOps, Azure administration, or a related area * Experience in management consulting and/or systems integration environments * Experience with containers and cloud-native platforms such as Azure Kubernetes Service, Kubernetes, Docker, or Azure Container Apps * Experience with AI evaluation, tracing, telemetry, content safety, responsible AI, and production support models * Experience implementing infrastructure as code with Bicep, Terraform, ARM templates, or comparable technologies * Strong communication, stakeholder management, and client-facing skills, with an interest in turning complex operational problems into scalable solutions Skills and experience ## Description Help shape how enterprise AI runs in the real world. As an AIOps/LLMOps Engineer, you'll build the automation, observability, and operational foundations that move generative AI solutions from promising prototypes to reliable production services on Microsoft Azure and Microsoft Foundry. Come Join Us You'll work hands-on across AI applications, models, data, cloud infrastructure, and operations. You will partner with architects and engineering teams to create secure, scalable delivery patterns, improve reliability and cost, and continuously raise the quality of AI services. If your experience spans some, but not all, of these areas, we still encourage you to apply. What you'll do * Build and operate reusable AIOps and LLMOps capabilities for enterprise AI solutions using Microsoft Foundry, Azure Machine Learning, and related Azure services. * Automate the lifecycle of models, prompts, agents, retrieval components, datasets, evaluations, and deployment configurations. * Create production automation using Python, PowerShell, Bash, C#, TypeScript, APIs, and infrastructure as code. * Implement CI/CD, testing, environment promotion, approvals, rollback, versioning, and traceability through Azure DevOps and/or GitHub Actions. * Establish observability for AI quality, reliability, performance, cost, safety, and business outcomes using tools such as Azure Monitor, Application Insights, OpenTelemetry, and MLflow. * Diagnose production issues and improve service health through alerts, runbooks, incident response, capacity planning, resiliency, and cost optimization. * Apply security, identity, data protection, responsible AI, content safety, auditability, and governance controls. * Collaborate across AI, data, application, cloud, security, and service management teams to transition solutions into supportable production services.