Capgemini
Conversational AI Engineer (LLM & GenAI)
Atlanta, GA, US · Senior · Full-time
Stay score
odds of building a lasting career here
Sponsors, but it's cap-subject — you still face the weighted lottery (~30% per draw at Level II). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →H-1B wage level
the lottery is wage-weighted — each level is one more entry
The bottom of this range ($80,000) is below the Level I prevailing wage of $91,915. An H-1B cannot be filed below the prevailing wage, so an offer at the floor of this band could not be sponsored as posted.
DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Atlanta-Sandy Springs-Roswell, GA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.
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About the role
- The ideal candidate will possess strong expertise in Large Language Models (LLMs), Natural Language Processing (NLP), Machine Learning, Generative AI, and Angular-based application development.
- Apply NLP techniques including intent recognition, text classification, sentiment analysis, entity extraction, summarization, and semantic search.
- Analyze large datasets and continuously improve model performance through experimentation and optimization.
Responsibilities
- Design, develop, and deploy conversational AI solutions leveraging 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.
- Develop prompt engineering strategies and optimize prompts to improve response quality, accuracy, and user experience.
- Evaluate, fine-tune, and optimize LLMs for business-specific applications.
- Utilize frameworks such as TensorFlow, PyTorch, and other AI/ML platforms to build scalable solutions.
- Deploy, monitor, and maintain production-grade AI/GenAI applications.
- Develop intuitive and responsive user interfaces for AI-powered experiences.
- Collaborate with backend and AI teams to seamlessly connect LLM and ML services with enterprise applications.
Requirements
- Strong expertise in Conversational AI, Generative AI, NLP, and Large Language Models (LLMs).
- Experience with LangChain or similar LLM orchestration frameworks.
- 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.
- Familiarity with Azure, AWS, or Google Cloud services for AI deployment and scaling.
Skills
- 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.
- Hands-on experience implementing RAG solutions using vector databases.
Compensation
- $80k-$90k
Benefits
- Manage the end-to-end lifecycle of AI and machine learning models using MLflow or similar MLOps tools.
- 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
- Other benefits as provided by local policy and eligibility
This listing is sourced directly from Capgemini's careers page and normalized into a canonical job model.