GenAI Solutions Architect

Job Title

GenAI Solutions Architect

Location

Remote + Quarterly Travel to Chicago, IL

  

Duration

Long-term Contract

Experience

8+ Years

Visa

, and EAD

Interview Process

1-2 rounds

Communication

Excellent Communication Skills – MUST HAVE

Background

Data Science / Machine Learning – MUST HAVE

 

Overview

We are seeking a highly technical GenAI Solutions Architect to join a growing AI Center of Excellence (CoE) focused on delivering enterprise-scale Generative AI solutions. This individual will be responsible for designing, prototyping, and evangelizing innovative AI architectures that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI frameworks, and advanced machine learning technologies.

The ideal candidate has a strong foundation in Machine Learning, Natural Language Processing (NLP), and/or Computer Vision, and has evolved into a solution architecture role where they work directly with business stakeholders to identify opportunities, build proof-of-concepts (POCs), secure funding, and transition successful solutions to engineering teams for production deployment.

Responsibilities

• Design and architect enterprise Generative AI solutions leveraging LLMs, RAG frameworks, and Agentic AI architectures.

• Partner with business leaders and technical stakeholders to identify high-value AI use cases and translate requirements into scalable solution designs.
• Build and demonstrate AI proof-of-concepts (POCs), MVPs, and prototypes to validate business value and technical feasibility.
• Lead solutioning efforts within an AI Center of Excellence (CoE) environment, evaluating emerging technologies and recommending best-fit architectures.
• Define end-to-end AI architecture including model selection, orchestration, vector databases, prompt engineering strategies, and deployment patterns.
• Work closely with engineering teams to transition approved solutions into production environments.
• Create technical presentations, architecture diagrams, and executive-level communications for both technical and non-technical audiences.
• Evaluate and recommend AI platforms, frameworks, and tooling based on business objectives and technical requirements.
• Stay current on emerging trends within Generative AI, Agentic AI, multimodal AI, and machine learning ecosystems.

Required Qualifications

• MUST HAVE DATA SCIENCE/ML BACKGROUND 

• 8+ years of experience in Software Engineering, Machine Learning, AI, or Solution Architecture roles.
• Strong technical background in Machine Learning, NLP, Computer Vision, or related AI disciplines.
• Hands-on experience architecting Generative AI solutions in enterprise environments.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
• Experience with Agentic AI frameworks and autonomous workflow orchestration.
• Deep understanding of Large Language Models (LLMs) and prompt engineering methodologies.
• Experience working within an AI Center of Excellence (CoE) or similar innovation-focused organization.
• Proven track record of building successful AI POCs and advancing them to funded initiatives and production implementations.
• Excellent communication, presentation, and stakeholder management skills.

Technical Requirements

Experience with several of the following technologies:

• Large Language Models (OpenAI, Claude, Gemini, Llama, etc.)
• RAG Architecture
• Agentic AI Frameworks
• Vector Databases:
• Pinecone
• Weaviate
• Chroma
• FAISS
• Google Vertex AI
• AWS SageMaker
• Hugging Face
• LangChain
• LangGraph
• LlamaIndex
• Python
• Machine Learning & Deep Learning Frameworks
• Cloud Platforms (AWS, Google Cloud Platform, Azure)
• API Design & Integration

Preferred Qualifications

• Experience leading enterprise AI transformation initiatives.
• Experience evaluating and selecting GenAI technologies for large organizations.
• Background working across multiple AI domains including NLP, Computer Vision, and Predictive Analytics.
• Experience estimating ROI and business value for AI investments.
• Experience presenting AI strategy and architecture recommendations to executive leadership.