Agentic AI Engineer – Workflow Orchestration & Prompt Engineer

Agentic AI Engineer role in Charlotte, NC (onsite) focused on workflow orchestration, prompt/context engineering, and reliable operational execution.

• Design, develop, and optimize multi-step prompt workflows that support AI agent activities such as reasoning, decision support, content generation, analysis, and task execution.
• Translate business problems into structured AI workflow designs by breaking complex tasks into logical stages and execution paths.
• Design and maintain reusable prompt libraries
  , workflow templates, and orchestration patterns, including standardized templates,
  version control
  , evaluation criteria, change tracking, and lifecycle management.
• Define workflow architecture covering prompts, context requirements, tool interactions, orchestration logic, handoffs, dependencies, and output requirements.
• Determine how information, memory, context, and intermediate outputs are managed throughout execution.
• Analyze execution logs
  , model outputs, and intermediate agent responses to identify root causes of failures, performance degradation, and inconsistent results.
• Troubleshoot issues across prompt design, context management, agent behavior, tool integrations, data pipelines, file structures, APIs, and execution environments.
• Evaluate workflow effectiveness using qualitative and quantitative measures; implement improvements to increase reliability, accuracy, efficiency, and user outcomes.
• Improve context engineering strategies to optimize retrieval, grounding, memory management, and response quality.
• Develop automation, scripts, and utilities to support workflow development, experimentation, testing, evaluation, monitoring, and operational efficiency.
• Perform data inspection, transformation, validation, and analysis to support workflow development and troubleshooting.
• Contribute to AI governance, risk management, quality assurance, and responsible AI practices by ensuring workflows operate within established standards and controls.
• Stay current on emerging AI technologies, agent frameworks, orchestration platforms, prompt engineering techniques, and industry best practices.

• Experience designing, implementing, and optimizing multi-step LLM
  , generative AI, and agentic workflows
  .
• Strong problem-solving ability to translate complex business challenges into scalable AI solutions
  .
• Expertise in prompt engineering
  , human-in-the-loop workflows, and AI performance optimization.
• Ability to troubleshoot and diagnose issues across prompts, agents, context management, integrations, and workflow execution.
• Proficiency in Python
  , APIs,
  JSON
  , Markdown
  , and working with structured and unstructured data.
• Experience using AI-assisted development tools such as Git Hub Copilot
  , Claude Code
  , Cursor
  , or similar platforms.
• Knowledge of agent orchestration frameworks, multi-agent architectures, and modern workflow orchestration patterns.
• Understanding of RAG
  , context engineering, memory management, tool calling, and agent planning methodologies.
• Experience integrating AI solutions with enterprise applications, automation platforms, cloud AI services, and business processes.
• Strong communication and collaboration with governance, risk, and responsible AI expertise, including evaluation, monitoring, compliance, and operational controls.

• Python
  , APIs, JSON, Markdown
• Git Hub Copilot, Claude Code, Cursor
• RAG, tool calling, multi-agent architectures

• Agentic AI & Workflow Orchestration: multi-step LLM/agent workflows, tool calling, handoffs, orchestration patterns.
• Prompt & Context Engineering: prompt design, RAG, grounding, context/memory management, human-in-the-loop patterns.
• Hands-On AI Engineering: Python, APIs, JSON, data integration, scripting, AI-assisted development.
• LLM Evaluation & Troubleshooting: testing workflows, diagnosing failures, analyzing outputs/logs, improving accuracy and reliability.
• Business-to-AI Solution Design: translating ambiguous business problems into scalable, structured, end-to-end AI solutions.