AI Agent Engineer

Remitly•Dayton, OH

9d•$78,800 - $131,300

About The Position

Are you excited to help operate and improve AI agents that deliver reliable, real‑world outcomes in production environments? Do you enjoy working at the intersection of automation, systems monitoring, and human oversight to ensure safe and high‑quality AI performance? About the Business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. About the Team: We are a newly formed Enterprise AI team focused on enabling agent-based solutions across the organization. We build and manage the environments, platforms, and guardrails that allow teams to create, test, and scale AI agents safely and efficiently turning experimentation into real business impact. We’re a team of curious builders and operators who are constantly exploring, learning, and applying new AI tools and approaches to solve real-world problems and improve how work gets done. About the Role: The AI Agent Engineer plays a critical role in ensuring AI agents run safely, reliably, and effectively within enterprise environments. This position supports the operational design, execution, and continuous optimization of AI agents and agent‑based workflows. The role emphasizes practical execution, system integration, monitoring, and governance controls rather than model development or research.

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

Nice To Haves

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

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 to ensure 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 the controlled rollout of AI capabilities