Senior AI Engineer - MLOps & Azure Platform

EisnerAmper; Melville (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

EisnerAmper is seeking a Senior AI Engineer specializing in MLOps and AIOps to deploy, operate, and optimize enterprise AI solutions on Azure. You will collaborate with AI Developers, Product Owners, Governance leaders, and Cloud Architects to ensure reliable, scalable, and cost-effective systems across tax, audit, advisory, and client-facing applications.

The role emphasizes secure, observable, and governed machine learning deployments that deliver real business impact, with a culture that

Qualifications

• 5-7+ years in MLOps and/or AIOps, ideally within Azure cloud environment
• Hands-on experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry
• Consulting/background with strong bias for action is a plus

Responsibilities

• Deploy and monitor AI models across Azure services with telemetry for performance, drift, and availability.
• Manage model upgrades including APIs and UIs with structured rollout, version control, and rollback support.
• Optimize performance and cost through testing, profiling, and tuning of inference infrastructure and pipelines.
• Implement MLOps pipelines for CI/CD and lifecycle management using Azure ML and GitHub Actions.
• Ensure compliant change management with auditability, security, and governance controls.

Skills

MLOps

AIOps

Azure ML

Synapse

Data Lake

App Services

Cosmos DB

Azure AI Foundry

Education

Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field

Job description

EisnerAmper is seeking a Senior AI Engineer specializing in MLOps and AIOps to deploy, operate, and optimize enterprise AI solutions on Azure. You will collaborate with AI Developers, Product Owners, Governance leaders, and Cloud Architects to ensure reliable, scalable, and cost-effective systems across tax, audit, advisory, and client-facing applications.

The role emphasizes secure, observable, and governed machine learning deployments that deliver real business impact, with a culture that