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# AI Platform Architect

- **Company:** Capgemini
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Salary:** $84,989.0 - $132,787.0
- **Contract:** Temporary contract
- **Skills:** JavaScript (Programming Language), Artificial Intelligence, Airflow, Amazon Web Services, BigQuery, Cloud Engineering, Distributed Systems, Data Flow Control, Monitoring of Systems, Python (Programming Language), Software Architecture, Cloud Services, Cloudera, Data Streaming, Google Cloud, Large Language Models, Multi-Agent Systems, AI Platforms, Kubernetes, Machine Learning Operations, Network Server, Serverless Computing
- **Published:** September 9, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a6003003a74d0361

## About the Role

Seeking an experienced GCP and AI Platform Architect to design and lead next-generation AI systems built on LLMs and agentic frameworks. This role focuses on architecting scalable, production-grade AI platforms across cloud environments, with a strong emphasis on RAG, agent orchestration, agent harness/skill building, observability, and gateway patterns., * 8+ years of software architecture experience with a strong focus on distributed systems.

 * Proven experience with LLMs, RAG architectures, and agentic systems, including agent harness and skill development.
 * Deep understanding of agent orchestration, asynchronous processing, and streaming architectures.
 * Strong hands-on expertise with Kubernetes and cloud-native/serverless architectures.
 * Experience designing AI platform components, including gateways, observability platforms, and agent infrastructure.
 * Proficiency in Python and JavaScript.
 * Strong communication, stakeholder management, and architecture storytelling skills., * Experience with multi-agent frameworks (e.g., LangGraph, ADK) and emerging agent ecosystems.
 * Familiarity with LLMOps, evaluation frameworks, and AI governance.
 * Hands-on experience with GCP services, including:
 + BigQuery
 + Cloud Composer
 + Dataflow
 + Dataproc
 + Cloud Functions

## Description

* Design end-to-end architectures for AI platforms leveraging RAG, agentic systems, and LLM-based applications.
 * Define and implement agentic patterns, including streaming, asynchronous workflows, multi-agent orchestration, and agent harness and skill development.
 * Architect platform components such as:
 + AI/LLM Gateways
 + Agent frameworks, identity layers, and skill orchestration
 + MCP gateways, servers, and tools
 + Observability and monitoring systems
 * Build scalable solutions on Kubernetes and serverless cloud services.
 * Lead architecture initiatives across Google Cloud Platform (GCP) and/or Amazon Web Services (AWS).
 * Drive best practices for the reliability, scalability, and performance of AI systems.
 * Translate complex AI capabilities into clear architectural narratives and business solutions.