GenAI Solutions Architect

Job Titile : GenAI Solutions Architect

Location: Remote with quarterly travel to Chicago, IL



Duration: 6+ Months

Job Summary

We are looking for an experienced GenAI Solutions Architect to design and implement enterprise-grade Generative AI solutions. The ideal candidate will have strong experience in AI/ML, LLMs, RAG architectures, Agentic AI, and cloud platforms, with a proven ability to take AI concepts from POCs through production.

Responsibilities

• Design and architect scalable Generative AI solutions for enterprise environments.
• Develop and implement Retrieval-Augmented Generation (RAG) architectures.
• Design Agentic AI solutions and autonomous workflow orchestration.
• Work with Large Language Models (LLMs) and develop effective prompt engineering strategies.
• Build AI POCs and help transition successful solutions into funded initiatives and production environments.
• Collaborate with AI Centers of Excellence, engineering teams, and business stakeholders.
• Evaluate emerging AI technologies, frameworks, and platforms.
• Provide technical leadership and communicate architecture decisions to technical and non-technical stakeholders.
• Integrate AI solutions with enterprise applications and APIs.

Required Qualifications

• 8+ years of experience in Software Engineering, Machine Learning, AI, or Solution Architecture.
• Strong 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 RAG architectures.
• Experience with Agentic AI frameworks and autonomous workflow orchestration.
• Strong understanding of LLMs and prompt engineering.
• Experience working within an AI Center of Excellence or similar innovation-focused organization.
• Proven experience taking AI POCs through production implementation.
• Excellent communication, presentation, and stakeholder management skills.

Technical Skills

Experience with several of the following:

• LLMs: 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 and Deep Learning Frameworks

Thanks & Regards,

Chebolu Raviteja (Lead Recruiter)



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