Senior AI Engineer — Voice & NLP (LLM/RAG)

Capgemini; Charlotte (NC); On-site; USD 54,000 - 85,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

Retirement benefits

Job summary

Tundra Technical Solutions is seeking a senior AI Engineer to design scalable LLM and NLP solutions for high-volume customer interactions. You will drive architecture, best practices, and innovation across voice AI systems.

Responsibilities include architecting AI-driven IVR systems, building NLP models for intent detection, and designing LLM workflows with prompt engineering and RAG. You will mentor offshore and junior AI engineers and collaborate with cross-functional teams.

Qualifications

• 12+ years of experience in AI/ML
• Very strong proficiency in Python
• Text classification
• Strong experience in data analysis using SQL
• Hands-on experience with LLMs
• Evaluation frameworks
• Retrieval-Augmented Generation (RAG)

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
• Design and deploy LLM workflows (prompt engineering, RAG, evaluation) for voice and chat use cases
• Lead development of agentic AI workflows for multi-step customer interactions
• Establish LLMOps best practices, including monitoring, evaluation, and lifecycle management
• Partner with IVR platform, speech engineering, and product teams
• Mentor offshore and junior AI engineers

Skills

AI/ML experience

Python

Text classification

SQL

LLMs

Evaluation frameworks

RAG

Tools

spaCy

Hugging Face Transformers

NLTK

Sentence-Transformers

LangGraph

AutoGen

CrewAI

Oracle

MySQL

SQLAlchemy

MLflow

Weights & Biases

BentoML

Airflow

Job description

Tundra Technical Solutions is seeking a senior AI Engineer to design scalable LLM and NLP solutions for high-volume customer interactions. You will drive architecture, best practices, and innovation across voice AI systems.

Responsibilities include architecting AI-driven IVR systems, building NLP models for intent detection, and designing LLM workflows with prompt engineering and RAG. You will mentor offshore and junior AI engineers and collaborate with cross-functional teams.