Advanced AI Solution Architect

Advanced AI Solution Architect

Job Description

Join the team behind iconic brands like Huggies®, Kleenex®, Cottonelle®, Scott®, Kotex®, Poise®, Depend®, and Kimberly-Clark Professional®.

 At Kimberly-Clark, it’s all here for you—innovation, growth, and the chance to make a real impact. 

Technology Roles 

You were made to create Better Care for a Better World: designing new technologies, diving into data, optimizing digital experiences, and constantly developing better, faster ways to get results.

You want to be part of a performance culture dedicated to building technology for a purpose that matters.

Here, you’ll work in an environment that promotes sustainability, inclusion, wellbeing, and career development while you help us deliver better care for billions of people around the world.  It starts with YOU. 

About You

In one of our technical roles, you’ll focus on winning with consumers and the market, while putting safety, mutual respect, and human dignity at the center.

Job responsibilities include:

We are seeking an experienced and forward-thinking Advanced AI Solution Architect to architect, scale, and govern enterprise-grade Generative AI and Agentic AI platforms that drive measurable business impact.

This role is ideal for a hands-on AI leader with deep expertise in large language models (LLMs), AI Agents, RAG systems, LLMOps, and enterprise AI governance — someone who combines strong technical depth with strategic architectural vision.

As a senior technical authority, you will lead the architecture, design, and productionization of our flagship AI platforms while actively contributing to enterprise AI governance through the Advanced AI Council.

You will partner with product, engineering, data, security, legal and enterprise architecture leaders to ensure our AI ecosystem is scalable, secure, observable, compliant, and built for long-term enterprise adoption.

To succeed in this role, you will need the following qualifications:

Required Qualifications

Architecture and Platform Leadership:


* Lead the architecture and evolution of enterprise-scale GenAI and Agentic AI platforms, including LLM-based systems, RAG architecture, AI Agents, and multimodal pipelines.


* Define and institutionalize reference architectures and reusable design patterns across AI platforms.


* Evaluate and select foundation models (open-source and commercial) based on business objectives, cost efficiency, performance, and risk posture.


* Design secure, resilient, high-performance cloud-native AI systems (Azure preferred) aligned with enterprise architecture and security standards.

Model Strategy and Optimization


* Fine-tune and optimize large language models using prompt engineering, LoRA, PEFT, transfer learning, and reinforcement learning techniques where applicable.


* Architect scalable RAG systems, including embedding strategies, vector database integration, and semantic retrieval optimization.
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