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# Software Engineer

- **Company:** Capgemini
- **Location:** Atlanta, GA, United States
- **Salary:** $68,911.0 - $161,544.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software as a Service, Computer Programming, Continuous Integration, Software Debugging, JSON, Python (Programming Language), Standard Sql, Systems Integration, Amazon Connect, Data Logging, Google Cloud, Genesys, Large Language Models, Prompt Engineering, Generative AI, Git, Low Latency, Data Management, Virtual Agents, Restful APIs, Webhooks, Docker
- **Published:** September 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=4976c9d6fddbb4ca

## About the Role

* Strong Python programing skills.
 * Good knowledge of REST APIs, JSON, webhooks and system integration.
 * Hands-on cloud application development, deployment, logging and monitoring experience in GCP cloud
 * Working knowledge of Git, CI/CD and Docker.
 * Good awareness of Generative AI, LLMs, prompt engineering, RAG and AI agents.
 * Basic SQL and data-handling skills.
 * Good communication, troubleshooting, and customer-service process understanding.
 * Strong analytical thinking, debugging, communication and learning agility.
 * Willing to learn and upskill on Agentic AI or Google Gemini Enterprise

Preferred Skills

 * Experience in a contact-center or conversational platform such as Genesys Cloud, NICE CXone, Amazon Connect, Dialogflow or a similar platform.
 * Basic Experience designing customer journeys, conversation flows.

## Description

* Develop and integrate Python-based services, APIs and AI-enabled applications.
 * Build agent workflows using prompts, tools, APIs, enterprise knowledge and structured data.
 * Deploy and operate applications on Google Cloud using secure, observable and repeatable engineering practices.
 * Configure and extend conversational and customer-experience use cases, including virtual agents, agent assistance and workflow automation.
 * Participate in discovery sessions, rapidly prototype solutions and translate business needs into working technical outcomes.
 * Test, troubleshoot and optimize agent behavior, integrations, latency, reliability and user experience.
 * Create technical documentation, deployment runbooks and clear demonstrations for delivery teams and clients.
 * Apply responsible AI, security, access-control and data-handling practices throughout the solution lifecycle.


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