AI Systems Engineer

7 days ago

vellore, India beBeeTechOps Full time

A successful Agentic & AI Tech Ops Engineer plays a pivotal role in ensuring the reliability, scalability, and efficiency of AI and agentic AI systems in production. This is an exciting opportunity for a proactive individual to manage deployments, monitor performance, troubleshoot issues, and implement best practices for Tech Ops/MLOps/LLMOps.Key ResponsibilitiesDeployment & Infrastructure:Deploy and manage AI models, agentic systems, and infrastructure across cloud (GCP, AWS, Azure) and on-prem.Implement CI/CD pipelines for AI/ML and agentic applications.Optimize cloud resources for cost and scalability.Monitoring & Incident Management:Build monitoring, logging, and alerting solutions for AI systems.Handle incident response, root cause analysis, and maintain runbooks.Automation & Operational Excellence:Automate deployments and maintenance using Python/Bash and IaC tools (Terraform, Ansible).Enforce security, compliance, and operational best practices.Collaboration & Documentation:Work with AI developers, data scientists, and architects for smooth production transitions.Maintain clear documentation and provide feedback on system performance.Required QualificationsBachelor's degree in Computer Science, Information Technology, Engineering, or related field.2–4+ years of experience in Tech Ops, DevOps, SRE, or MLOps roles.Hands-on experience with cloud platforms (GCP—Vertex AI, AWS, Azure).Proficient in Python/Bash scripting, CI/CD tools (Jenkins, GitLab CI, GitHub Actions).Experience with Docker, Kubernetes, monitoring tools (Prometheus, Grafana, ELK, Datadog).Knowledge of networking, security, and IaC principles.Strong troubleshooting and communication skills.Preferred QualificationsMaster's degree and cloud certifications.Experience in MLOps/LLMOps and AI/ML frameworks (TensorFlow, PyTorch).Familiarity with agentic AI concepts, vector databases, and data pipeline tools (Airflow, Kubeflow).Agile environment experience.

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