Senior Software Engineer

Capgemini • Chicago, IL

22d • Hybrid

About The Position

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. This role is a Hybrid opportunity based in New Jersey, Atlanta, Chicago, Dallas. At Capgemini, you will collaborate with cross-functional teams to deliver innovative technology solutions that drive business value and enhance client experiences. You will contribute to the design, development, and continuous improvement of scalable, high-quality solutions in a dynamic and collaborative environment. We are seeking a highly motivated Conversational AI Engineer with experience in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and NLP-based solutions. The ideal candidate will have hands-on experience building, deploying, and optimizing AI-powered applications while collaborating with cross-functional stakeholders to solve complex business problems.

Requirements

• 2 to 4 years of experience in Software Engineering, Backend Development, Machine Learning, NLP, or related fields.
• 1 to 2+ years of hands-on experience working with LLM APIs such as OpenAI, Anthropic, Azure OpenAI, or Hugging Face models.
• Proven experience building and deploying RAG-based applications.
• Strong understanding of prompt engineering, model evaluation techniques, and AI application lifecycle management.
• Experience working directly with business stakeholders and managing technical requirements.
• Proficiency in Python and relevant AI/ML libraries and frameworks.
• Strong understanding of NLP concepts and transformer-based architectures (GPT, BERT, Llama, etc.).
• Experience with vector databases, embeddings, semantic search, and retrieval systems.
• Knowledge of cloud platforms, preferably AWS, for deploying and managing AI applications.
• Hands-on experience with Docker and Kubernetes for scalable application deployment.
• Experience in data preprocessing, augmentation, and synthetic data generation techniques.
• Excellent analytical thinking and problem-solving skills.

Nice To Haves

• Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar AI orchestration frameworks.
• Experience deploying applications using MCP (Model Context Protocol).
• Familiarity with MLOps practices, CI/CD pipelines, and model monitoring.
• Understanding of observability, security, and governance practices for AI systems.
• Experience working with vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or Azure AI Search.

Responsibilities

• Design, develop, and deploy conversational AI solutions using Large Language Models (LLMs) such as OpenAI, Anthropic, and Hugging Face models.
• Build, optimize, and maintain Retrieval-Augmented Generation (RAG) pipelines to improve response quality and domain-specific knowledge retrieval.
• Conduct model evaluation, prompt engineering, and performance testing to ensure high-quality AI outputs.
• Collaborate with business stakeholders, product teams, and developers to translate business requirements into scalable AI solutions.
• Develop NLP-powered applications involving text parsing, classification, sentiment analysis, summarization, and text generation.
• Manage end-to-end AI application deployment on cloud platforms, with a focus on AWS and cloud-native architectures.
• Deploy and manage AI workloads using containerization and orchestration technologies such as Docker and Kubernetes.
• Design and implement data preparation workflows, including data cleaning, labeling, augmentation, and synthetic data generation.
• Monitor, troubleshoot, and optimize AI systems in production environments.
• Implement AI governance, scalability, and reliability best practices.
• Work with MCP (Model Context Protocol) frameworks and related integrations for AI application deployment and orchestration.

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
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed