About this role
It's fun to work in a company where people truly BELIEVE in what they're doing!
Job Description: Deployment & Infrastructure Management:
• Deploy, configure, and manage AI models, agentic systems, and supporting infrastructure in cloud (e.g., GCP) and on-premise environments. • Implement and maintain CI/CD pipelines for AI/ML models and agentic applications (MLOps/Agent Ops). • Manage and optimize cloud resources, ensuring cost-effectiveness and scalability for AI workloads. • Collaborate with infrastructure teams to ensure network, storage, and compute resources meet the demands of AI systems.
Monitoring, Logging & Alerting:
• Develop and implement comprehensive monitoring, logging, and alerting solutions for AI agents and infrastructure to ensure high availability and performance. • Proactively identify and address potential issues, performance bottlenecks, and anomalies in production AI systems. • Track key operational metrics and create dashboards for system health and performance.
Incident Response & Troubleshooting:
• Provide operational support for production AI systems, including incident response, root cause analysis, and resolution of technical issues. • Develop and maintain runbooks and standard operating procedures for common operational tasks and incident management. • Participate in on-call rotations as needed to support critical AI services.
Automation & Operational Excellence:
• Automate routine operational tasks, deployment processes, and system maintenance activities using scripting (e.g., Python, Bash) and automation tools. • Contribute to the development and enforcement of operational best practices, security standards, and compliance requirements for AI systems. • Work with development teams to improve the deployability, manageability, and observability of AI applications.
Collaboration & Documentation:
• Collaborate effectively with AI developers, data scientists, AI architects, and other stakeholders to ensure smooth transitions from development to production. • Maintain clear and comprehensive documentation for system configurations, operational procedures, and troubleshooting guides. • Provide feedback to development teams on operational aspects and system performance. Preferred Qualifications & Experience:
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field. • 4-7+ years of experience in a MLOps or Agent Ops role, preferably supporting AI/ML or data-intensive applications. • Hands-on experience with cloud computing platforms (e.g., Google Cloud Platform - especially Vertex AI) and managing cloud-based infrastructure. • Proficiency in scripting languages such as Python, Bash, or PowerShell for automation. • Experience with CI/CD tools and practices (e.g., Bitbucket, GitLab CI, GitHub Actions). • Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration. • Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack, Datadog, Google Cloud Monitoring, Langfuse). • Understanding of networking concepts, security best practices, and infrastructure-as-code (IaC) principles (e.g., Terraform, Ansible). • Strong troubleshooting and problem-solving skills with an analytical mindset. • Excellent communication skills and ability to work collaboratively in a team environment. • A proactive approach to identifying and resolving issues and improving system reliability. • Master's degree in a relevant field. • Specific experience in MLOps or Agent Ops, including deploying and managing machine learning models or large language model applications in production. • Familiarity with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn). • Understanding of agentic AI concepts and the operational challenges they present. • Experience with managing vector databases or other specialized data stores for AI. • Knowledge of data pipeline tools (e.g., Apache Airflow, Kubeflow Pipelines). • Relevant cloud certifications (e.g., Google Cloud Professional ML Engineer). • Experience working in an agile development environment.
Why Join Us?
• Play a critical role in operationalizing cutting-edge Agentic AI and AI systems for a global industry leader.
• Gain hands-on experience with the latest MLOps, Agent Ops, and cloud technologies. • Work in a dynamic, innovative, and collaborative AI Center of Excellence. • Opportunity to significantly impact the reliability and efficiency of transformative AI solutions. • Competitive salary, bonus, and benefits package.