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Agile AI System Architect

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AI Infrastructure EngineerWe are seeking an expert to design and implement the infrastructure for our AI systems.The ideal candidate will have hands-on experience with cloud platforms, CI/CD tools, and automation frameworks.Key Responsibilities:Deployment & Management:Deploy and manage AI models and agentic systems across cloud and on-prem infrastructure.Implement continuous integration and deployment pipelines for AI applications.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.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 Skills:Bachelor's in CS, IT, Engineering, or related field.2–4+ years in Tech Ops, DevOps, SRE, or MLOps roles.Hands-on experience with cloud platforms (GCP, 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).