Senior AI Engineer - MLOps/AIOps on Azure

EisnerAmper; Minneapolis (MN); On-site; USD 140,000 - 180,000; Full time

Job summary

EisnerAmper, a leading accounting and advisory firm, seeks a Senior AI Engineer to design, deploy, and govern enterprise-grade AI solutions on Azure.

You will collaborate with AI developers, product owners, governance leaders and cloud architects to ensure reliable, scalable deployments across tax, audit, advisory, and client-facing applications.

This role emphasizes observability, security, and cost optimization, with a culture of merit-based advancement and a commitment to work-life balance.

Qualifications

• 5-7+ years in MLOps/AIOps, ideally within Azure cloud environments.
• Hands-on experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry.
• Bachelor's degree in a technical field is preferred.

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 continuous integration, deployment, and lifecycle management using Azure ML and GitHub Actions.
• Ensure compliant change management for all AI-related deployments, 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, a leading accounting and advisory firm, seeks a Senior AI Engineer to design, deploy, and govern enterprise-grade AI solutions on Azure.

You will collaborate with AI developers, product owners, governance leaders and cloud architects to ensure reliable, scalable deployments across tax, audit, advisory, and client-facing applications.

This role emphasizes observability, security, and cost optimization, with a culture of merit-based advancement and a commitment to work-life balance.