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# Agentic AI Engineer - Software Engineer

- **Company:** Capgemini
- **Location:** Atlanta, GA, United States
- **Experience:** Experienced
- **Salary:** $53,580.0 - $122,400.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Electronic Data Interchange (EDI), Identity and Access Management, JSON, Python (Programming Language), Software Engineering, Systems Integration, Scripting, Google Cloud, Large Language Models, Prompt Engineering, Agentic-AI, Gitlab-ci, Kubernetes, Low Latency, Data Management, Virtual Agents, Restful APIs, Docker
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/agentic-ai-engineer-software-engineer-atlanta-ga--97de0bd8-6d46-4387-bed2-1f1ca33d226c

## About the Role

Artificial Intelligence (AI), Software Engineering, Team Player, Coaching, Mentoring, Software Development, Application Programming Interface (API), Python Programming/Scripting Language, Artificial Intelligence (AI), Structured Data, * 4 plus years experience working on Python: scripting, API integration, and application-level development

 * Cloud Platforms: hands-on experience with at least one major cloud provider (GCP preferred; Strong Azure or AWS also acceptable) compute, networking, IAM, and basic service deployment
 * Experience in deployment with containerization and orchestration (Docker, Kubernetes)
 * Understanding/Exp of CI/CD concepts and tools (GitLab CI/CD or equivalent)
 * Understanding working exp of REST APIs and JSON-based data exchange
 * Prior exposure to GenAI concepts (LLMs, prompt engineering, embeddings)
 * Familiarity with Google Cloud console navigation and Vertex AI / Agent Platform tools Preferred

## Description

* 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.
 * 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.