Principal AI Engineer 3

Overview

Lead the architecture and production deployment of enterprise-scale generative AI and agentic AI systems. The role covers cloud AI infrastructure, multi-agent orchestration, LLMOps, security, governance, and technical leadership.

What you'll do

• Design scalable, secure cloud-native AI infrastructure across AWS, Azure, or GCP.
• Architect RAG, semantic search, fine-tuning, and multi-agent orchestration solutions.
• Establish agent guardrails, human-in-the-loop checkpoints, and evaluation frameworks.
• Design LLMOps/MLOps pipelines for ingestion, evaluation, versioning, and deployment.
• Implement observability, alerting, rollback, and AI infrastructure cost-management strategies.
• Enforce security, governance, permissions, and auditability for autonomous AI systems.
• Mentor technical teams and advise executives on AI architecture and business value.

What you'll need

• Deep expertise in at least one of AWS, Azure, or GCP.
• Experience delivering enterprise-scale generative AI and LLM solutions.
• Experience building or architecting multi-agent systems.
• Knowledge of MCP and Agent-to-Agent communication protocols.
• Strong MLOps/LLMOps experience, including CI/CD, versioning, evaluation, and observability.
• Knowledge of AI governance, security, responsible AI, IAM, RBAC, and network segmentation.
• Bachelor's, Master's, or PhD in Computer Science, Engineering, or a related field.

Nice to have

• Cloud AI/ML certifications such as AWS Solutions Architect, AWS AI Practitioner, GCP Professional Cloud Architect, or Azure AI Engineer.

Details

• Location: Bangalore, India.
• Work mode: Hybrid.
• Employment type: Regular.
• Language: English proficiency at C2 level.