AI System Operations Specialist

4 days ago

hubballi, India beBeeOperations Full time

Technical Operations Engineer for AI and Agentic SystemsAs a seasoned Technical Operations Engineer, you will play a pivotal role in ensuring the reliability, scalability, and efficiency of AI and agentic systems in production. This includes managing deployments, monitoring performance, troubleshooting issues, and implementing best practices for tech ops/mlops/llmops.Key ResponsibilitiesDeployment & Infrastructure:Deploy and manage AI models, agentic systems, and infrastructure across cloud platforms (GCP, AWS, Azure) and on-premise environments.Implement Continuous Integration/Continuous Deployment pipelines for AI/ML and agentic applications using Python/Bash scripting and IaC tools like Terraform and Ansible.Optimize cloud resources for cost and scalability while ensuring security and compliance standards are met.Monitoring & Incident Management:Design and implement monitoring, logging, and alerting solutions for AI systems to ensure proactive issue detection and resolution.Develop incident response plans, conduct root cause analysis, and maintain runbooks to ensure seamless operations.Automation & Operational Excellence:Automate deployments and maintenance tasks using Python/Bash scripting and IaC tools like Terraform and Ansible.Enforce security, compliance, and operational best practices across all AI and agentic systems.Collaboration & Documentation:Work closely with AI developers, data scientists, and architects to ensure smooth production transitions and knowledge sharing.Maintain clear documentation and provide feedback on system performance to drive continuous improvement.Required QualificationsBachelor's degree in Computer Science, Information Technology, Engineering, or a related field.2-4+ years of experience in Technical Operations, DevOps, SRE, or MLOps roles.Hands-on experience with cloud platforms (GCP - Vertex AI, AWS, Azure).Proficient in Python/Bash scripting, CI/CD tools like Jenkins, GitLab CI, GitHub Actions, and IaC tools like Terraform and Ansible.Experience with Docker, Kubernetes, monitoring tools like Prometheus, Grafana, ELK, and Datadog.Knowledge of networking, security, and IaC principles.Strong troubleshooting and communication skills.Preferred QualificationsMaster's degree and relevant cloud certifications.Experience with MLOps/LLMOps and AI/ML frameworks like TensorFlow and PyTorch.Familiarity with agentic AI concepts, vector databases, and data pipeline tools like Airflow and Kubeflow.Agile environment experience.

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