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# AI Engineer

- **Company:** ApTask
- **Location:** Charlotte, NC, United States
- **Experience:** Experienced
- **Salary:** $114,400.0 - $124,800.0
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, XML Schema, Agile Methodology, Artificial Intelligence, Audit Trail, Automation of Tests, Continuous Integration, Data Mining, Graph Database, Monitoring of Systems, JSON, Python (Programming Language), Machine Learning, MongoDB, Neo4j, Parsing, Redis, Search Technologies, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Generative AI, Agentic-AI, Git, Event Driven Architecture, Machine Learning Operations, Model Explainability, Restful APIs, Intelligent Document Processing, Human in the Loop, Microservices
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/81f647c2-53fb-4b38-8463-646bd0e77d5e/ai-engineer

## About the Role

* 5 years of experience in Artificial Intelligence (AI), Machine Learning (ML), Generative AI, or Intelligent Automation solutions.
 * 5 years of hands-on experience with Python and AI development frameworks, including LangChain, LangGraph, Google ADK, and agent-based architectures.
 * 3 years of experience implementing Document AI / Intelligent Document Processing (IDP) solutions involving OCR, PDF parsing, data extraction, confidence scoring, rule-based validation, semantic matching, fuzzy comparison, and API integration.
 * 3 years of experience designing and developing REST APIs, Microservices, and JSON/XML schema mappings for enterprise integrations.
 * Strong experience building and deploying LLM-powered applications, AI agents, RAG (Retrieval-Augmented Generation) solutions, and workflow automation platforms.
 * Experience implementing confidence scoring, validation frameworks, human-in-the-loop (HITL) workflows, and exception handling mechanisms.
 * Familiarity with workflow orchestration platforms, business process automation, and event-driven architectures.
 * Strong understanding of data privacy, PII handling, AI governance, model explainability, auditability, and responsible AI controls.
 * Experience with prompt engineering, vector databases, embeddings, and semantic search technologies.
 * Proficiency in Git, CI/CD pipelines, Agile methodologies, and automated testing practices.
 * Familiarity with MongoDB, Neo4j Knowledge Graphs, Redis, and vector databases.
 * Knowledge of MLOps, AI observability, model monitoring, and evaluation frameworks.
 * Strong analytical, troubleshooting, and problem-solving skills.
 * Excellent communication and collaboration abilities within cross-functional teams.