Senior AI Engineer

Description: On-site 4/1 in Charlotte, NC Our client seeks a Senior AI Engineer to lead IVR and conversational AI initiatives for large-scale customer interactions in telecommunications and digital services. The role requires strong pre-LLM experience and the ability to bridge classical ML and NLP with modern LLM architectures. The engineer will define standards, guide architecture, and mentor junior engineers while partnering across platform, speech engineering, and product teams. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $55.00 to $60.00/hr. w2 Responsibilities: • Architect and develop AI-driven IVR and conversational systems using Python. • Build NLP models for text classification and clustering to support intent detection and call routing. • Perform data analysis using SQL on large-scale IVR and interaction datasets. • Design and deploy LLM workflows including prompt engineering, RAG, and evaluation for voice and chat use cases. • Lead development of agentic AI workflows for multi-step customer interactions. • Establish LLMOps best practices for monitoring, evaluation, and lifecycle management. • Partner with IVR platform, speech engineering, and product teams. • Mentor offshore and junior AI engineers. Experience Requirements: • 5+ years of experience in AI and ML, including pre-LLM era work. • Strong proficiency in Python. • Proven expertise in NLP, including text classification and clustering. • Strong experience in data analysis using SQL. • Hands-on experience with LLMs including prompt engineering, evaluation frameworks, and Retrieval-Augmented Generation. • Good to have: experience with agentic AI and multi-agent orchestration. • Good to have: experience with LLMOps or MLOps in production environments. • Familiarity with IVR platforms and speech technologies such as ASR, NLU, and TTS. • Relevant tools and libraries: NumPy, Pandas, Scikit-learn, XGBoost, spaCy, Hugging Face Transformers, NLTK, Sentence-Transformers, LangChain, LlamaIndex, OpenAI SDK, LangGraph, AutoGen, CrewAI, Oracle, MySQL, SQLAlchemy, FAISS, Pinecone, Weaviate, Qdrant, MLflow, Weights & Biases, BentoML, Airflow.