AI Agent Engineer

About the Role The AI Agent Engineer is responsible for ensuring AI agents run safely, reliably, and effectively within enterprise environments. The role focuses on operational design, execution, continuous optimization, system integration, monitoring, and governance controls rather than model development or research. Responsibilities Support the operational design and execution of AI agents and multi‑agent workflows used across business and technology teams. Monitor agent behavior, outputs, and reliability in production environments, identifying performance issues, errors, or unexpected behaviors. Tune and optimize agent configurations, prompts, workflows, and execution logic to improve output quality and operational stability. Integrate AI agents with enterprise systems, APIs, Model Context Protocols (MCP), and internal or external data sources. Implement and maintain runtime guardrails, escalation paths, and human‑in‑the‑loop controls for safe and compliant AI operation. Investigate and resolve operational issues related to agent performance, data access, or system integration. Document workflows, configurations, and operational procedures to support repeatability and governance. Collaborate with AI engineers, data teams, platform teams, and business stakeholders to support controlled rollout of AI capabilities. Requirements 1–2 years of experience in a technical or operational role such as data operations, application support, system operations, or AI platform support. Basic understanding of AI concepts such as agents, prompts, workflows, APIs, and automation. Experience working with APIs, enterprise systems, or data integrations. Ability to monitor systems, analyze outputs, and identify patterns or anomalies. Strong attention to detail and a methodical approach to operating production systems. Clear written and verbal communication skills, including the ability to document processes and issues. Comfort working in environments that blend automation with human oversight and escalation. Preferred Qualifications Exposure to AI platforms, LLM‑based systems, or automation tools. Experience working with guardrails, approval workflows, or human‑in‑the‑loop processes. Familiarity with data governance, security, or compliance concepts. Experience supporting production environments with reliability or uptime considerations. What This Role Is (and Is Not) Operational, hands‑on role focused on running and improving AI agents in production. Bridge between AI engineering, data, and business teams. Focused on reliability, quality, and safe execution. Not an AI research or model‑training role. Not a traditional software engineering role. Not a pure data science or analytics position. Career Growth Provides a foundation for future roles in AI operations, platform engineering, reliability engineering, or advanced AI solution positions as enterprise AI adoption expands. Benefits Summary Includes medical insurance, life assurance policies, family benefits, long‑service awards, celebratory allowances, flexible benefits plan, employee assistance program, flexible working arrangements, learning and development resources, and a comprehensive national base pay range. Additional benefits are available based on location. EEO Statement We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. #J-18808-Ljbffr