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.