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Capgemini

Conversational AI Engineer, LLM, GenAI

Capgemini

. Design, develop, and deploy conversational AI solutions leveraging LLMs such as GPT, Llama, and other foundation models .

Posted 10/16/2026full-timeAtlanta • United StatesMid-LevelSenior💰 $80,000 - $90,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Demonstrates expertise in designing and deploying conversational AI solutions using LLMs, with a strong focus on NLP techniques and model optimization. Proficient in managing the lifecycle of AI/ML models and integrating AI capabilities into web applications.

Highest-signal resume keywords
Conversational AILarge Language Models (LLMs)NLP TechniquesPython ProgrammingMLOps Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
AI DevelopmentData AnalysisMachine LearningPrompt EngineeringRAG ArchitecturesModel OptimizationText ClassificationSentiment AnalysisEntity ExtractionSemantic Search
Tools & Technologies
TensorFlowPyTorchMLflowAngularAzureAWSGoogle Cloud PlatformLangChainVector DatabasesAI/ML Platforms
Industry Keywords
Generative AIConversational AIAI-Powered ApplicationsProduction-Grade SolutionsEnterprise Applications

Tech Stack

Tools & technologies
AngularAWSAzureCloudGoogle Cloud PlatformPythonPyTorchTensorflow

About the role

Key responsibilities & impact
  • Design, develop, and deploy conversational AI solutions leveraging LLMs such as GPT, Llama, and other foundation models
  • Build intelligent chatbots, virtual assistants, and AI-powered applications for enterprise use cases
  • Implement RAG architectures using vector databases and semantic search technologies
  • Develop prompt engineering strategies and optimize prompts
  • 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/ML models using MLflow or similar MLOps tools
  • Deploy, monitor, and maintain production-grade AI/GenAI applications
  • Ensure reliability, scalability, and operational excellence of deployed AI solutions
  • Integrate conversational AI capabilities into Angular web applications
  • 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 for performance, governance, and scalability
  • Deploy AI and machine learning models on Azure, AWS, or Google Cloud Platform
  • Stay current with Generative AI, Conversational AI, LLM, NLP, and emerging AI technologies
  • Develop proof-of-concepts, prototypes, and pilot solutions

Requirements

What you’ll need
  • 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

Benefits

Comp & perks
  • 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
  • Possible variable incentives, bonuses, or commissions