Solutions Consultant

Overview

Sr. Engineer II, ML Ops will establish enterprise-grade AI operations (MLOps/LLMOps) and, once operational practices are team-owned, lead a transition into emerging AI research and innovation.

What you'll do

• Own end-to-end model lifecycle design, including versioning, CI/CD, artifact registry, environment promotion, and deployment automation.
• Implement LLMOps practices such as prompt versioning, testing harnesses, regression detection, governance, and rollback.
• Build automated retraining (scheduled, drift-triggered, and manual intervention points) and self-healing mechanisms for degradation remediation.
• Define evaluation, monitoring, and observability for ML and LLM systems, including dashboards, alerts, and incident response playbooks.
• Govern AI release readiness using an AI Definition of Done, operational evidence capture, approval gates, audit trails, and safe rollout patterns.
• Lead proof-of-concepts and convert successful experiments into production-ready capabilities for advanced/agentic AI and RAG.

What you'll need

• 7+ years software engineering experience.
• 5+ years leading AI/ML initiatives at production scale.
• Deep hands-on expertise in 4+ of: MLOps/LLMOps, evaluation frameworks, drift monitoring, and CI/CD for ML and model governance.
• Strong Python experience for writing, reviewing, and debugging production systems.
• Experience deploying AI in regulated environments such as healthcare or fintech (or equivalent).
• Proven ability to establish practices teams adopt and operate independently.

Details

• Location: Bangalore, India.