Software Engineer

Capgemini•Atlanta, GA

6d•$68,911 - $161,544•Hybrid

About The Position

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 hands-on AI Engineer to enhance, optimize, and scale our existing AI platform built on Claude Sonnet and Model Context Protocol (MCP). The ideal candidate will be responsible for improving AI agents, MCP tools, enterprise integrations, response quality, system performance, security, and overall platform scalability. This role requires strong technical expertise in Generative AI, agentic workflows, and enterprise system integration.

Requirements

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Minimum 3+ years of software development experience using Python and/or TypeScript/Node.js.
Hands-on experience building and deploying LLM-based or Generative AI applications.
Strong understanding of Model Context Protocol (MCP), AI agents, tool calling, and agent orchestration.
Experience working with Claude, OpenAI, or similar Large Language Model (LLM) platforms.
Experience integrating AI applications with APIs, databases, and enterprise systems.
Solid knowledge of RAG architectures, vector databases, embeddings, and prompt engineering.
Strong debugging, analytical, problem-solving, and communication skills.

Nice To Haves

Experience with LangChain, LangGraph, Semantic Kernel, or similar AI development frameworks.
Knowledge of AI observability and evaluation frameworks.
Experience with prompt optimization and AI response quality improvement.
Understanding of authentication, authorization, and security best practices for AI applications.
Experience deploying and managing production-grade AI solutions in cloud environments.
Familiarity with CI/CD pipelines, containerization, and scalable application architectures.

Responsibilities

Enhance, maintain, and optimize MCP-based AI applications and intelligent agents.
Design, develop, and improve MCP servers, tools, and integrations.
Integrate AI solutions with enterprise systems, APIs, databases, and knowledge repositories.
Improve prompt engineering strategies, context management, and AI response accuracy.
Design, develop, and optimize RAG (Retrieval-Augmented Generation) solutions.
Implement monitoring, logging, observability, and security controls across AI applications.
Troubleshoot AI agent behavior, tool execution issues, and platform performance bottlenecks.
Support deployment, testing, maintenance, and continuous enhancement of AI capabilities.
Collaborate with cross-functional teams to deliver scalable and reliable AI-powered solutions.
Ensure compliance with enterprise security, authentication, and access control standards.