Conversational AI Engineer (LLM & GenAI)

Capgemini • Atlanta, GA

6d • $80,000 - $90,000

About The Position

Capgemini is seeking a Conversational AI Engineer to design, develop, and deploy intelligent AI-powered conversational solutions. The role focuses on production-ready applications using Large Language Models (LLMs), Natural Language Processing (NLP), machine learning, Generative AI, Retrieval-Augmented Generation (RAG), and Angular. The engineer will build enterprise chatbots and virtual assistants, integrate AI services with modern web applications, and deploy scalable solutions in cloud environments such as Azure, AWS, or Google Cloud Platform.

The position involves hands-on work across the AI and machine-learning lifecycle, including prompt engineering, model evaluation and optimization, MLOps, cloud deployment, monitoring, and maintenance. The engineer will collaborate with backend and AI teams, review solution architectures for governance and scalability, and develop prototypes and proofs of concept to assess emerging technologies. The position is located in Atlanta, Georgia.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• At least 5 years of hands-on experience in AI development, data analysis, and machine learning.
• Proven experience building and deploying production-grade AI/ML solutions.
• Strong expertise in Conversational AI, Generative AI, NLP, and LLMs.
• Experience with LangChain or similar LLM orchestration frameworks.
• Hands-on experience implementing RAG solutions using vector databases.
• Experience with GPT, Llama, or other commercial or open-source LLMs.
• Strong proficiency in Python and software engineering best practices.
• Experience with Angular and modern web application development.
• Knowledge of MLflow or similar MLOps platforms for model lifecycle management.
• Experience with TensorFlow, PyTorch, or equivalent machine-learning frameworks.
• Familiarity with Azure, AWS, or Google Cloud services for AI deployment and scaling.

Responsibilities

• Design, develop, and deploy conversational AI solutions using LLMs such as GPT, Llama, and other foundation models.
• Build enterprise chatbots, virtual assistants, and AI-powered applications.
• Implement RAG architectures using vector databases and semantic search technologies.
• Develop and optimize prompts to improve response quality, accuracy, and user experience.
• Evaluate, fine-tune, and optimize LLMs for business-specific applications.
• Apply NLP methods including intent recognition, text classification, sentiment analysis, entity extraction, summarization, and semantic search.
• Use TensorFlow, PyTorch, and other AI/ML platforms to build scalable solutions.
• Analyze large datasets and improve model performance through experimentation and optimization.
• Manage the end-to-end AI and machine-learning model lifecycle using MLflow or similar MLOps tools.
• Deploy, monitor, and maintain production-grade AI and Generative AI applications.
• Ensure reliability, scalability, and operational excellence of deployed AI solutions.
• Integrate conversational AI capabilities into web applications using Angular and develop intuitive, responsive user interfaces.
• Collaborate with backend and AI teams to connect LLM and ML services with enterprise applications.
• Implement real-time conversational experiences and intelligent user interactions.
• Validate and review LLM solution architectures for performance, governance, and scalability.
• Deploy AI and machine-learning models on Azure, AWS, or Google Cloud Platform.
• Stay current with developments in Generative AI, Conversational AI, LLMs, NLP, and related technologies.
• Develop proofs of concept, prototypes, and pilot solutions to evaluate new technologies.

Benefits

• Paid time off, including vacation (12–25 days depending on employee grade), company-paid holidays, personal days, and sick leave.
• Medical, dental, and vision coverage, or provincial healthcare coordination in Canada.
• Retirement savings plans, such as a 401(k) in the U.S. or RRSP in Canada.
• Life and disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.
• The role may be eligible for variable incentives, bonuses, or commissions, depending on the position and applicable laws.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior