Lead AI Engineer role focused on deploying and managing AI models and infrastructure in cloud and on-premise environments with emphasis on MLOps and Agent Ops.

Role: Lead AI Engineer

Location: Chennai, India / India

Experience:

4-7+ years of experience in a MLOps or Agent Ops role
Experience supporting AI/ML or data-intensive applications

Key Skills:

AI models deployment
Agentic systems
Cloud computing platforms
Google Cloud Platform
Vertex AI
CI/CD pipelines
MLOps
Agent Ops
Python
Bash
PowerShell
Bitbucket
GitLab CI
GitHub Actions
Docker
Kubernetes
Prometheus
Grafana
ELK Stack
Datadog
Google Cloud Monitoring
Langfuse
Networking concepts
Infrastructure-as-code
Terraform
Ansible
TensorFlow
PyTorch
scikit-learn
Vector databases
Apache Airflow
Kubeflow Pipelines
Agile development

Qualification:

Bachelor’s degree in Computer Science, Information Technology, Engineering, or related technical field
Master's degree in a relevant field

Role Focus:

Deploy, configure, and manage AI models and agentic systems in cloud and on-premise environments
Implement and maintain CI/CD pipelines for AI/ML models and agentic applications
Manage and optimize cloud resources for AI workloads
Collaborate with infrastructure teams to meet AI system resource demands
Develop and implement monitoring, logging, and alerting solutions for AI agents and infrastructure
Identify and address performance bottlenecks and anomalies in production AI systems
Track operational metrics and create dashboards for system health and performance
Provide operational support including incident response and root cause analysis
Develop and maintain runbooks and standard operating procedures
Automate routine operational tasks and deployment processes
Contribute to operational best practices, security standards, and compliance
Work with development teams to improve deployability, manageability, and observability
Collaborate with AI developers, data scientists, AI architects, and stakeholders
Maintain documentation for system configurations, operational procedures, and troubleshooting
Provide feedback to development teams on operational aspects and system performance

Additional responsibilities:

Participate in on-call rotations to support critical AI services

Nice to have:

Specific experience deploying and managing machine learning models or large language model applications in production
Familiarity with AI/ML frameworks and libraries
Understanding of agentic AI concepts and operational challenges
Experience managing vector databases or specialized AI data stores
Relevant cloud certifications such as Google Cloud Professional ML Engineer

Other:

Play a critical role in operationalizing cutting-edge Agentic AI and AI systems for a global industry leader
Gain hands-on experience with latest MLOps, Agent Ops, and cloud technologies
Work in a dynamic, innovative, and collaborative AI Center of Excellence
Opportunity to impact reliability and efficiency of transformative AI solutions
Competitive salary, bonus, and benefits package

Lead AI Engineer

Skills Required

Description