Senior AI Agent Engineer

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title:
Senior AI Agent Engineer
Location:
Charlotte, NC(Remote)
Duration: 24 Months + Extension
Bill Rate: $69/hour (C2C)
Job Type: W-2, 1099, C2C
Client:
To Be Discussed Later
Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Design, develop, and harden production-grade AI agents across the end-to-end detect → store → plan → remediate → deploy lifecycle.
Build and orchestrate Finder, Planner, and Executor agents to identify issues, prioritize remediation, execute approved actions, validate changes, and support controlled deployments.
Develop agent orchestration and tool integrations using Model Context Protocol (MCP), tool calling, agent frameworks, and workflow engines such as Temporal.
Develop and integrate agents with the Actionable Observation store, Overwatch state machine and prioritization capabilities, and operator console.
Integrate agents with Git Lab pipelines, Git Lab CI/CD, JFrog Artifactory, canary deployment workflows, and Tenable Vulnerability Management (UVM) as a vulnerability-finding source.
Expose and consume enterprise knowledge graphs containing data lineage and environment context through MCP, ensuring agents have governed, read-only access to relevant information.
Implement event processing, data storage, and state management using Kafka, MongoDB, SQL, and SQLite.
Develop and query knowledge graphs using Neo4j and Cypher to support contextual retrieval, dependency analysis, and remediation planning.
Implement automated code-change workflows, AI-assisted code generation, test generation, and lockdown-test practices to validate remediation changes before deployment.
Apply context engineering and specification-driven development to improve agent accuracy, consistency, traceability, and maintainability.
Embed human-approval gates, audit trails, access controls, and AI governance controls throughout agent design, execution, and deployment.
Ensure autonomous workflows comply with enterprise security standards, change-management processes, deployment controls, and production-readiness requirements.
Support vulnerability remediation and software version-currency initiatives using CVE, EPSS, CVSS, End-of-Life (EOL), and End-of-Support (EOS) considerations.
Implement controlled deployment patterns, including canary releases and incremental rollouts, to reduce operational risk.
Troubleshoot agent execution failures, integration issues, workflow exceptions, and deployment problems; perform root-cause analysis and implement corrective actions.
Monitor and improve agent reliability, performance, scalability, and observability using Dynatrace or comparable tools where applicable.
Collaborate with application development, infrastructure, cybersecurity, Dev Sec Ops , architecture, and production support teams to integrate agents into existing workflows.
Document reusable agent patterns, technical designs, integration approaches, governance controls, onboarding procedures, and operational best practices.
Coach application, infrastructure, and security teams on agent onboarding, secure usage, human oversight, and adoption of the autonomous operating model.
Participate in technical design reviews, code reviews, automated testing, release planning, and continuous improvement initiatives.
Own AI agent solutions across requirements, design, development, integration, testing, deployment, monitoring, and ongoing enhancement.

Minimum 7+ years of experience in software engineering or production application development, delivering and supporting enterprise-grade solutions.
Minimum 1–2+ years of hands‑on experience developing LLM‑based applications, Generative AI solutions, AI agents, or agentic…