AI Agent SW Eng

Description: Hybrid 3 days onsite in either Rockville, MD or Mclean, VA The organization seeks an AI Agent Software Engineer to architect and build agentic systems, orchestration frameworks, and observability that streamline the SDLC. The role develops production-grade AI agents, integrates with internal tooling, and establishes governance and performance analytics. The engineer will drive AI-first automation, partnering across teams to deliver measurable developer productivity and reliability improvements in a financial services context.We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $65.00 to $70.00/hr. w2Responsibilities: Develop production-grade AI agents that remove manual handoffs across the SDLC. Create custom integrations and CLI tools to provide agents deep understanding of internal systems and codebases. Design comprehensive testing strategies to ensure agent reliability and output quality. Implement Golden Path scaffolding that embeds organizational standards into new projects. Build AI solutions that improve codebase navigation, documentation, and developer workflows. Identify workflow bottlenecks and deliver measurable impact through intelligent automation. Shape SDLC evolution by identifying AI-first opportunities and proving outcomes through experimentation. Architect and maintain production infrastructure for agent deployment, lifecycle management, and scaling. Develop agent frameworks, templates, and SDKs that accelerate agent development. Create a governed Model Context Protocol catalog enabling compliant agent-to-agent and agent-to-MCP communication. Implement governance controls for agent behavior, permissions, and system access. Design and implement metrics, monitoring, and logging for AI agents and development workflows. Build dashboards with actionable insights into developer productivity, tool adoption, and agent performance. Establish KPIs and measurement frameworks to quantify 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 investments. 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 best practices. Rapidly prototype solutions to validate use cases and prove value. Communicate data-driven insights to stakeholders through clear visualizations and reports. Experience Requirements: 5 to 7 or more years of software engineering experience building production systems. Proven experience building agentic systems using LLM orchestration frameworks. Hands-on expertise with AI-powered development tools such as code assistants and AI-enhanced editors. Strong foundation in SDLC, system design, and internal tooling development. Experience with observability tools and practices including metrics collection, logging frameworks, and dashboard development. Proficiency with Java, Python, and JavaScript or TypeScript. Experience with Angular and Spring Boot. Experience with CI/CD platforms and AWS cloud infrastructure. Experience with monitoring and observability tools such as Prometheus, Grafana, and CloudWatch. Demonstrated ability to identify automation opportunities and deliver measurable outcomes.

Created: 2026-04-02