Agentic & AI Tech Ops Engineer

Agentic & AI Tech Ops Engineer

Location:

Role Overview:

Agentic & AI Tech Ops Engineer

Key Responsibilities

• Deployment & 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 Qualifications

• Bachelor’s in CS, IT, Engineering, or related field.
• 2–4+ years in Tech Ops, DevOps, SRE, or MLOps roles.
• Hands-on 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 Qualifications

• Master’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.