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 solutions using large language models, NLP, machine learning, generative AI, and Angular-based applications, including Retrieval-Augmented Generation (RAG) architectures and scalable deployments in cloud environments. The position is located in Atlanta, Georgia.

The engineer will build and maintain enterprise chatbots, virtual assistants, and AI-powered applications; improve model and prompt performance; integrate conversational capabilities into web applications; and manage the lifecycle of AI/ML solutions through deployment, monitoring, and maintenance. The role also involves evaluating emerging technologies through proofs of concept, prototypes, and pilots, and collaborating with backend and AI teams to deliver reliable, scalable solutions.

Capgemini describes itself as a global business and technology transformation partner with 340,000 team members in more than 50 countries. The role’s posted base compensation range is $80,000–$90,000. Regular full-time employees may be eligible for benefits under local policy, including paid time off, holidays, personal days, sick leave, medical, dental and vision coverage, retirement savings plans, life and disability insurance, and employee assistance programs.

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 techniques 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 lifecycle of AI and machine learning models using MLflow or similar MLOps tools.
• Deploy, monitor, and maintain production-grade AI/GenAI applications.
• Ensure the reliability, scalability, and operational excellence of deployed AI solutions.
• Integrate conversational AI into modern 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.
• Keep current with advancements in Generative AI, Conversational AI, LLMs, NLP, and emerging AI technologies.
• Develop proofs of concept, prototypes, and pilot solutions to evaluate new technologies.

Benefits

• Paid time off, including vacation of 12–25 days depending on employee grade, company-paid holidays, personal days, and sick leave, subject to policy.
• Medical, dental, and vision coverage, subject to local policy and eligibility.
• Retirement savings plans such as a 401(k) in the U.S. or RRSP in Canada, subject to local policy and eligibility.
• Life and disability insurance, subject to local policy and eligibility.
• Employee assistance programs, subject to local policy and eligibility.
• Other benefits as provided by local policy and eligibility.

What This Job Offers

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