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Associate Manager, AI & Agentic Engineering – AIOps/LLMOps Engineer
Avanade. Build and operate reusable AIOps and LLMOps capabilities for enterprise AI solutions using Microsoft Foundry, Azure Machine Learning, and related Azure services .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and operating AIOps and LLMOps capabilities using Azure services, with strong skills in automation, CI/CD practices, and observability for AI solutions. Proven ability to collaborate across diverse teams while ensuring security, governance, and high-quality outcomes in AI and cloud environments.
Highest-signal resume keywords
Azure Machine LearningPython AutomationCI/CD ImplementationDevOps PracticesAI Lifecycle Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonPowerShellBashC#TypeScriptInfrastructure As CodeAutomated TestingAI/ML Solutions DeploymentObservability PracticesIncident Response
Soft Skills
Problem-SolvingAnalytical CapabilitiesCollaborationCommunicationInterpersonal Skills
Tools & Technologies
Microsoft FoundryAzure DevOpsGitHub ActionsAzure MonitorApplication InsightsOpenTelemetryMLflowAzure Kubernetes ServiceDockerTerraform
Certifications & Qualifications
Microsoft Azure AI CertificationMicrosoft Azure DevOps CertificationMicrosoft Azure Administration Certification
Industry Keywords
AIOpsLLMOpsCloud EngineeringMLOpsSite Reliability EngineeringProduction SupportGovernance ControlsContent SafetyResponsible AISystems Integration
Tech Stack
Tools & technologiesAzureCloudDockerKubernetesPythonTerraformTypeScript
About the role
Key responsibilities & impact- 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 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
Requirements
What you’ll need- 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
- 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
- Demonstrated ability to operate strategically and tactically
- Commitment to innovation, continuous learning, and delivering high-quality client outcomes
- Microsoft certification in Azure AI, Azure DevOps, Azure administration, or a related area preferred
- Experience in management consulting and/or systems integration environments preferred
- Experience with containers and cloud-native platforms such as Azure Kubernetes Service, Kubernetes, Docker, or Azure Container Apps preferred
- Experience with AI evaluation, tracing, telemetry, content safety, responsible AI, and production support models preferred
- Experience implementing infrastructure as code with Bicep, Terraform, ARM templates, or comparable technologies preferred
- Travel may be required based on client demand
- Ability to work evenings and/or weekends periodically to support project deliverables, client needs, or operational priorities
Benefits
Comp & perks- Medical coverage
- Dental coverage
- Vision coverage
- Life insurance
- Long-term disability coverage
- 401(k) plan
- Bonus opportunities
- Paid holidays
- Paid time off
- Flexible work environment
- Limitless learning and growth opportunities
- Inclusive and diverse culture
- Mentoring and collaboration opportunities