The Role
As an AI Data Engineer specializing in MLOps and AIOps, you will play a critical role in deploying, operating, and optimizing enterprise-grade AI solutions built on Azure. You will collaborate closely with AI Developers, Product Owners, Governance leaders, and Cloud Architects to ensure these systems are reliable, scalable, and cost-effective.
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 measurable business value.
What 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
What We're Looking ForBasic Qualifications
- Bachelor's degree in Computer Science, Engineering, Data Science, or related technical field
- 3+ years of hands-on experience in MLOps and/or AIOps, ideally within an Azure cloud environment
- Demonstrated expertise 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
- Experience with Workflow Design: Prompt flow, automation pipelines, and human-in-the-loop systems
- Knowledge of Post-Training Techniques: Fine-tuning, instruction tuning, RLHF, and domain adaptation
- Proficiency with Azure DevOps, App Insights, Log Analytics, Key Vault, and Managed Identity integration
- Experience with tools for inference performance testing and profiling (e.g., locust, K6, or custom scripts)
- Strong understanding of Model Evaluation: Performance metrics, benchmark development, and A/B testing frameworks
- Knowledge of model observability, telemetry, and incident response for AI systems
Application Question(s):
- Do you hold a Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field?
- Do you have 3 or more years of hands-on experience in MLOps and/or AIOps?
- Have you worked with Azure ML, Synapse, Data Lake, App Services, Cosmos DB, and Azure AI Foundry?
- Have your firm changes not exceeded 50% of your total years of professional experience?
- How many years of hands-on MLOps and/or AIOps experience do you have?
- Salary budget is INR 3000000 - 3500000Max what are your expectations?
Work Location: In person
