It's fun to work in a company where people truly BELIEVE in what they're doing

Job Description:
Deployment & Infrastructure Management:
Deploy, configure, and manage AI models, agentic systems, and supporting infrastructure in cloud (e.g., GCP) and on-premise settings.
Implement and maintain CI/CD pipelines for AI/ML models and agentic applications (MLOps/Agent Ops).
Manage and optimize cloud resources, ensuring cost-effectiveness and scalability for AI workloads.
Collaborate with infrastructure teams to ensure network, storage, and compute resources meet the demands of AI systems.​

Monitoring, Logging & Alerting:
Develop and implement comprehensive monitoring, logging, and alerting solutions for AI agents and infrastructure to ensure high availability and performance.
Proactively identify and address potential issues, performance bottlenecks, and anomalies in production AI systems.
Track key operational metrics and create dashboards for system health and performance.

Incident Response & Troubleshooting:




Provide operational support for production AI systems, including incident response, root cause analysis, and resolution of technical issues.
Develop and maintain runbooks and standard operating procedures for common operational tasks and incident management.
Participate in on-call rotations as needed to support critical AI services.

Automation & Operational Excellence:
Automate routine operational tasks, deployment processes, and system maintenance activities using scripting (e.g., Python, Bash) and automation tools.
Contribute to the development and enforcement of operational best practices, security standards, and compliance requirements for AI systems.
Work with development teams to improve the deployability, manageability, and observability of AI applications.

Collaboration & Documentation:
Collaborate effectively with AI developers, data scientists, AI architects, and other stakeholders to ensure smooth transitions from deve

📌 Lead Ai Engineer Chennai
🏢 Ingram Micro
📍 Chennai