AI Data Engineer MLOps & AIOps

Key Responsibilities

• 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

Nice to Haves

• 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 inference performance testing and profiling tools (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

Work Structure

• 14 days/month in office no more than 2 consecutive WFH days
• Work hours: 12:30 PM to 9:30 PM IST
• Maximum commute from home to office: 1 hour
• Interview process: 3 virtual rounds + 1 in-person round

Location Preference

Mumbai-based candidates preferred. Bangalore will be considered. Local candidates prioritized, but relocation candidates are welcome. Candidates relocating with their family are eligible for reimbursement covering: