Senior Agentic AI Systems Engineer (Compliance & Licences)- US Hybrid Charlotte, NC

We are seeking a Senior Agentic AI Systems Engineer to design, build, and operate production-grade AI agent systems that augment and automate real business workflows. This role goes beyond prompt engineering or demo-level prototypes. You will own agentic systems end-to-end-from architecture and integration with existing services, to reliability, evaluation, and long-term operation. You'll work closely with product, platform, and domain experts to deliver agentic capabilities that are trustworthy, scalable, and measurable, while helping define how agentic systems are built across the organization. What You'll Do

• Design, build, and operate agentic systems that reliably complete real tasks, not just answer questions.
• Architect agents that support planning, memory, tool use, and multi-step execution, selecting appropriate patterns (single-agent, multi-agent, workflow-driven, human-in-the-loop) based on problem constraints and risk.
• Balance autonomy with control by designing agents that are predictable, debuggable, secure, and aligned with business goals.
• Build agents using modern frameworks (e.g., LangGraph, LangChain, Semantic Kernel, AutoGen, or equivalent), implementing structured outputs, tool-calling, reflection, and state management.
• Design and implement MCP- and/or RAG-based integrations as first-class mechanisms for how agents access tools, data, and context.
• Enforce security, consent, access control, and observability across all agent-tool interactions, partnering with platform teams to establish and evolve MCP integration standards.
• Integrate agentic systems into existing services and platforms via APIs and backend services, owning production readiness end-to-end.
• Define what "good" looks like for agents using clear metrics (e.g., accuracy, success rate, latency, cost, failure modes), and use those metrics to drive continuous improvement.
• Build automated evaluation pipelines (offline tests, synthetic data, regression checks) and instrument agents with tracing, logging, and observability to support debugging and iteration in production.
• Design fallback, recovery, and human-escalation mechanisms for failure scenarios, proactively identifying and mitigating failure modes.
• Establish architectural standards and best practices for agentic development, raising the technical bar through design reviews, documentation, mentorship, and knowledge sharing.
• Partner with product and domain stakeholders to shape solutions, make informed trade-offs, and ensure agentic systems deliver meaningful business impact., You will work on agentic systems in the context of

• Knowledge of SBOM standards (especially CycloneDX, but also SPDX), and supply chain security
• Knowledge of cybersecurity principles, threat modeling, and common attack vectors in software supply chains
• Experience as maintainer of an inner-source and/or open-source project
• Experience leveraging CI/CD practices
• Familiarity with containerization technologies

These domains require agents that operate on real, evolving data, integrate deeply with existing systems, and meet a high bar for correctness, traceability, and user trust. Required Experience

• 5+ years of professional software engineering experience, with a strong backend or systems background.
• Proven experience building LLM-powered applications beyond prototypes.
• Hands-on experience designing and implementing agentic systems, including agents, workflows, MCP-based tool integration, and RAG.
• Strong proficiency in Python (or similar agent-oriented languages) and experience building production APIs or services.
• Experience designing systems with observability, evaluation, and operational ownership in mind.