Location

This role is a Hybrid opportunity based in New jersey, Atlanta, Chicago, Dallas

About the job you're considering

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.

Overview

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.

Key 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.

Required Qualification

• 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.

Preferred Qualification

• 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.

The base compensation range for this role in the posted location is: $73,150 to $174,000

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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