Jobs · Information Technology · Maryland

AI Agent & Infrastructure - Lead Engineer

FINRA · Rockville, MD · 3 wk ago
HybridInformation Technology$114k/yrFull-time

Key Responsibilities

  • AI Agent Development & Automation
  • Create production-grade AI agents that eliminate manual handoffs across the SDLCCreate custom integrations and CLI tools that give agents deep understanding of internal systems and codebasesDesign comprehensive testing strategies to ensure agent reliability and output qualityImplement "Golden Path" scaffolding that embeds organizational standards into new projectsBuild AI solutions that improve codebase navigation, documentation, and developer workflowsIdentify workflow bottlenecks and deliver measurable impact through intelligent automation
  • Shape SDLC evolution by identifying AI-first opportunities and proving outcomes through experimentation

Agent Infrastructure & Platform

  • Architect and maintain production infrastructure supporting agent deployment, lifecycle management, and scaling
  • Develop agent frameworks, templates, and SDKs that accelerate agent development
  • Create governed Model Context Protocol (MCP) catalog enabling compliant agent-to-agent and agent-to-MCP communication
  • Implement governance controls for agent behavior, permissions, and system access

Observability & Performance Analytics

  • Design and implement metrics, monitoring, and logging infrastructure for AI agents and development workflows
  • Build dashboards that provide actionable insights into developer productivity, tool adoption, and agent performance
  • Establish KPIs and measurement frameworks to quantify the impact of AI-powered automation
  • Create alerting and anomaly detection systems to ensure reliability of agents and tooling
  • Analyze telemetry data to identify optimization opportunities and guide strategic investment decisions

Collaboration & Impact

  • Partner across teams to drive adoption of AI-powered tooling and process transformation
  • Stay current with LLM technologies and coach colleagues on AI-assisted development and automation best practices
  • Rapidly prototype solutions to validate use cases and prove value quickly
  • Communicate data-driven insights to stakeholders through clear visualizations and reports

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