Conversational AI Engineer

Capgemini is seeking a Conversational AI Engineer in Atlanta, GA (onsite) to design, build, and deploy production-ready conversational AI solutions. The role focuses on leveraging LLMs, NLP, ML/GenAI, RAG architectures, and cloud deployment, along with development of Angular-based web experiences and end-to-end AI/ML lifecycle management.

Responsibilities

• Design, develop, and deploy conversational AI solutions using Large Language Models (LLMs) such as GPT, Llama, and other foundation models.
• Build intelligent chatbots, virtual assistants, and AI-powered applications for enterprise use cases.
• Implement Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies.
• Create prompt engineering strategies and optimize prompts to improve response quality, accuracy, and user experience.
• Evaluate, fine-tune, and optimize LLMs to support business-specific applications.
• Apply NLP techniques including intent recognition, text classification, sentiment analysis, entity extraction, summarization, and semantic search.
• Use frameworks such as TensorFlow, PyTorch, and other AI/ML platforms to build scalable solutions.
• Analyze large datasets and drive continuous model improvement 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 to ensure operational excellence.
• Integrate conversational AI capabilities into modern web applications using Angular.
• Develop intuitive and responsive user interfaces for AI-powered experiences.
• 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 to support performance, governance, and scalability.
• Deploy AI and machine learning models on cloud platforms such as Azure, AWS, or Google Cloud Platform.
• Stay current with advancements in Generative AI, Conversational AI, LLMs, NLP, and emerging AI technologies.
• Develop proof-of-concepts, prototypes, and pilot solutions to assess new technologies.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
• 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 Large Language Models (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/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.

Technologies

• Large Language Models (LLMs), GPT, Llama
• Natural Language Processing (NLP), Machine Learning, Generative AI
• Retrieval-Augmented Generation (RAG), vector databases, semantic search technologies
• TensorFlow, PyTorch
• MLflow, LangChain
• Python, Angular
• Azure, AWS, Google Cloud Platform

Compensation

USD 80,000 - 90,000 per year

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation 12-25 days depending on grade, company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility