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# Senior Software Engineer - Forward Deployed

- **Company:** Capgemini
- **Location:** Houston, TX, United States
- **Experience:** Expert
- **Salary:** $82,082.0 - $193,440.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, BigQuery, Cloud Computing, Cloud Engineering, Information Engineering, Software Debugging, DevOps, Search Technologies, Software Engineering, Systems Integration, AI Infrastructure, Model Garden (Google Cloud), Enterprise Software Applications, Chatbots, Retrieval-Augmented Generation, Multi-Agent Systems, Agentic-AI, Information Technology, Low Latency, Data Management, Terraform
- **Published:** October 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=4e28134f5cbb3a99

## About the Role

* At least 10+ years of experience in Software Engineering, AI/ML, Cloud Engineering, or Data Engineering.

 * Strong experience with GCP, Vertex AI, Vertex AI Agent Builder, ADK, and Model Garden.

 * Advanced Python development skills and experience building enterprise applications.

 * Hands-on experience with Agentic AI, multi-agent systems, Conversational AI, and CX solutions.

 * Experience implementing RAG, vector databases, embeddings, and enterprise knowledge integrations.

 * Experience with Terraform, cloud infrastructure, networking, and security.

 * Knowledge of evaluation frameworks, observability, debugging, and AI system optimization.

 * Experience integrating AI solutions with enterprise systems and APIs.

 * Experience working in Agile/Scrum environments.

 * Strong communication, stakeholder management, and problem-solving skills.

 * Bachelor's degree in Computer Science, Engineering, or related field.

 * Master's degree or PhD preferred.

## Description

* Design and deploy Agentic AI and Conversational AI solutions using Vertex AI Agent Builder and ADK.

 * Develop multi-agent workflows and integrate them with enterprise applications, APIs, and data platforms.

 * Build and optimize RAG solutions leveraging BigQuery, AlloyDB, and vector search technologies.

 * Implement secure integrations using MCP and cloud-native GCP services.

 * Develop evaluation, monitoring, and observability frameworks for AI systems.

 * Deploy and manage AI infrastructure using Terraform and modern DevOps practices.

 * Optimize agent performance, reasoning, tool selection, latency, and user experience.

 * Collaborate directly with client teams to deliver scalable, secure, and business-focused AI solutions.

 * Translate business requirements into production-ready AI architectures.

 * Participate in Agile delivery, client meetings, and technical design discussions.