Artificial Intelligence Data Engineer

Job Description

At EisnerAmper, we look for individuals who welcome new ideas, encourage innovation, and are eager to make an impact. Whether you're starting out in your career or taking your next step as a seasoned professional, the EisnerAmper experience is one-of-a-kind. You can design a career you'll love from top to bottom we give you the tools you need to succeed and the autonomy to reach your goals.

Join the EisnerAI team, a fast-growing organization within EisnerAmper that is redefining how professional services harness the power of Artificial Intelligence. As an AI Engineer specializing in MLOps and AIOps, you will play a critical role in deploying, operating, and optimizing enterprise-grade AI solutions built on Azure, collaborating closely with AI Developers, Product Owners, Governance leaders and Cloud Architects to ensure these systems are reliable, scalable, and cost-effective across tax, audit, advisory, and client-facing applications. This role goes beyond traditional DevOps it's about engineering AI into the fabric of enterprise operations, enabling secure, observable, and governed machine learning deployments that deliver real business impact.

What Work You Will be Responsible For:

• Deploy and monitor AI models across Azure services with robust 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.

Basic Qualifications

• Bachelors degree in Computer Science, Engineering, Data Science, or related technical field
• 3+ years in MLOps and/or AIOps, ideally within Azure cloud environment with hands-on experience with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry

Preferred/Desired Qualifications

• Consulting background with a strong bias for action.
• Workflow Design: Prompt flow, automation pipelines, and human-in-the-loop systems
• Post-Training Techniques: Fine-tuning, instruction tuning, RLHF, and domain adaptation
• Azure DevOps, App Insights, Log Analytics, Key Vault, and Managed Identity integration.
• Tools for inference performance testing and profiling (e.g., locust, K6, or custom scripts).
• Model Evaluation: Performance metrics, benchmark development, and A/B testing frameworks
• Understanding of model observability, telemetry, and incident response for AI systems.

Preferred Location: Mumbai

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.