Agentic AI Engineer

Hoffman & Hoffman Inc • Charlotte, NC

14h

About The Position

This role involves designing, building, and implementing autonomous AI agents that can reason, plan, and take action across the business. These agents will transform complex business goals into executable steps, integrate with existing systems, and enhance the experience for both employee-owners and customers. The position requires architecting agentic systems from scratch, including perception, planning, memory, and tool-use components, to autonomously complete multi-step workflows across various platforms. A key aspect is leveraging LLM capabilities by integrating frameworks like LangChain, Semantic Kernel, AutoGen, CrewAI, and LangGraph with the company's data hub and operational systems. Ensuring agent reliability in production through robust monitoring, observability, evaluation pipelines, logging, and safety controls is crucial. The role also entails collaborating with leadership, sales, and operations to translate business needs into agentic workflows and demonstrate impact through relevant KPIs. Continuous experimentation, feedback gathering, and iteration are expected to improve agent performance, along with comprehensive documentation of architectures, design decisions, and lessons learned.

Requirements

• A strong software engineering foundation with real production chops in Python and backend or data systems.
• Hands-on generative AI / agentic AI experience, including at least 1 year building with LLM-based agents, tool use, or multi-agent systems.
• Working fluency with one or more agentic/LLM stacks (LangChain, Semantic Kernel, AutoGen, CrewAI, LangGraph) and a major cloud AI platform (Azure OpenAI, Google Cloud, AWS, or equivalent).
• Solid grasp of prompt engineering, RAG, and context/memory management for LLM applications.
• Experience integrating AI with REST/GraphQL APIs, databases, message buses, and event-driven or microservices architectures.
• Familiarity with MLOps/AIOps — CI/CD, monitoring, cost controls, and lifecycle management for AI workloads.

Nice To Haves

• Designed or operated autonomous agents in complex domains (operations, customer support, finance, healthcare, marketing automation, etc.).
• Background in applied ML, reinforcement learning, or planning/decision-making algorithms.
• Real-world knowledge of AI safety, governance, and compliance — data privacy, access control, human-in-the-loop workflows.

Responsibilities

• Architect agentic systems from the ground up — perception, planning, memory, and tool-use components that complete multi-step workflows autonomously across APIs, internal services, and enterprise applications.
• Turn LLM capability into business leverage by integrating frameworks like LangChain, Semantic Kernel, AutoGen, CrewAI, and LangGraph with our data hub and operational systems.
• Make agents trustworthy in production — build the monitoring, observability, evaluation pipelines, logging, and safety controls that let us deploy with confidence instead of crossed fingers.
• Sit at the table with leadership, sales, and operations, translate what they actually need into agentic workflows, and prove impact with KPIs that move the business — not vanity metrics.
• Run experiments, gather feedback, and iterate fast to keep pushing agent performance forward.
• Document the craft — architectures, design decisions, limits, and lessons — so the whole company compounds on what you build.

Benefits

• You're an owner from day one. We're 100% employee-owned — the tools you build create value you directly share in.
• Entrepreneurial, not corporate. Fewer meetings, faster decisions, shorter distance between idea and production.
• Real problems, real users. Your agents will be used by your own colleagues and our customers — you'll see the impact, hear the feedback, and produce the fix the same week.
• Industry-leading ambition. We're not chasing AI trends. We're building the tools our industry will wish it had — alongside teammates who are as fired up about it as you are.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 11-50 employees