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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Hiring: Gen AI Architect at Charlotte, NC - **Company:** Realtech Services - **Location:** Charlotte, NC, United States - **Experience:** Experienced - **Salary:** $85,000.0 - $95,000.0 - **Contract:** Temporary to permanent - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Business Software, Software as a Service, Cloud Computing, Databases, Continuous Integration, Information Leak Prevention, Python (Programming Language), Machine Learning, Tensorflow, Software Construction, Software Deployment, Software Engineering, Google Cloud, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Scikit Learn, Information Technology, HuggingFace, Machine Learning Operations, Virtual Agents, Software Version Control, Microservices - **Published:** August 10, 2026 - **Apply:** https://www.careerjet.com/jobad/us42474a727b5b2374d03e5ed339b1236f ## About the Role * Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. * 8+ years of experience in Machine Learning Engineering, AI Engineering, Software Engineering, or Technology Architecture. * 3+ years of hands-on experience designing and implementing Generative AI and LLM-based solutions. * Proven experience designing and delivering Agentic AI, autonomous agents, or multi-agent systems. * Strong background in developing, deploying, serving, and monitoring machine learning and deep learning models. * Advanced programming experience in Python and familiarity with software engineering best practices. * Hands-on experience with ML frameworks such as PyTorch, TensorFlow, Scikit-learn, or Hugging Face. * Strong knowledge of LLMs, RAG, prompt engineering, context engineering, embeddings, vector databases, and tool/function calling. * Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud, along with APIs, microservices, containers, and CI/CD. * Knowledge of MLOps, LLMOps, AI security, responsible AI, model governance, data privacy, and production AI system monitoring. ## Description * Define the architecture and technical strategy for Generative AI, Agentic AI, LLM, and ML solutions. * Design and implement single-agent and multi-agent systems for enterprise use cases. * Develop AI agents capable of reasoning, planning, task execution, tool calling, and workflow orchestration. * Design and implement Retrieval-Augmented Generation solutions using structured and unstructured enterprise data. * Integrate AI agents with APIs, databases, microservices, SaaS platforms, and business applications. * Lead the selection, evaluation, fine-tuning, deployment, and optimization of LLMs and ML models. * Establish MLOps and LLMOps practices covering CI/CD, model versioning, monitoring, testing, and governance. * Implement AI guardrails to address hallucinations, prompt injection, data leakage, unauthorized actions, and unsafe outputs. * Define evaluation and observability frameworks to measure model quality, agent performance, accuracy, latency, cost, and reliability. * Lead architecture reviews, proof-of-concepts, production deployments, technical documentation, and mentoring of AI and ML engineering teams. ## Related Videos - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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