AgentOps Engineer – AI Managed Services

Location: Singapore

About The Role Keep AI-powered services running at scale. As an AgentOps Engineer , you will manage the reliability, performance, and operational health of enterprise AI agents in production. You will play a critical role in monitoring agent behavior, optimizing costs, managing releases, and ensuring AI solutions remain secure, reliable, and business-ready after go-live.

Key Responsibilities- Operate, monitor, and support AI agents, copilots, and Agentic Managed Services platforms in production environments.

• Design and implement observability, monitoring, incident response, release management, and operational support frameworks for AI solutions.
• Monitor agent accuracy, latency, availability, exception rates, user feedback, token consumption, and operational performance.
• Manage prompt, workflow, and agent releases, including rollback strategies, production controls, and readiness checks.
• Support AI FinOps activities through usage tracking, cost visibility, performance optimization, and consumption reporting.
• Develop operational runbooks, reliability standards, and lifecycle controls to ensure scalable and supportable AI services.
• Partner with Agentic Engineers, AI Quality Engineers, Solution Architects, and AMS teams to continuously improve reliability, security, and cost efficiency. Required Qualifications- Proven experience in DevOps, Site Reliability Engineering (SRE), or production operations.
• Experience with monitoring, observability, and operational support tools.
• Experience managing incidents, releases, production support, and service operations.
• Strong understanding of reliability, performance, automation, and operational excellence practices.
• Excellent problem-solving and stakeholder management skills. Preferred Qualifications- Experience supporting AI, Generative AI, copilots, agents, or intelligent automation platforms.
• Knowledge of cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Experience with CI/CD pipelines, Infrastructure as Code (Terraform, Bicep, or equivalent), and platform engineering practices.
• Familiarity with AI observability, AI FinOps, cost optimization, and performance monitoring.
• Experience working with enterprise platforms such as SAP, Salesforce, ServiceNow, or SuccessFactors.