Generative AI Solution Architect

Job Title: Gen AI Solution Architect (Hybrid)

Location: Glendale, CA 3 days a week

Duration: 24 months

Experience required : 5 - 20 Years

Must Have:

• Experience building Generative AI solutions within AWS
• Python
• Snowflake Cortex

Platform / Stack

You will work with technologies that include Snowflake Cortex, Python, AWS , and SQL.

Qualifications Required :

• Minimum of 7 years of related experience in AI/ML, software development, and designing scalable AI solutions.
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, Electrical/Electronics Engineering, or a related field, or equivalent work experience.
• Extensive background in AI, with a focus on developing robust, scalable, and innovative Generative AI solutions.
• Proficiency in Python, SQL, and relevant AI libraries and frameworks.
• Hands-on experience with multiple LLMs, chatbot development, vector databases, and RAG-based architectures.
• Experience building and deploying AI solutions on cloud platforms such as Azure, AWS, and Google Cloud.
• Expertise in query optimization and validation testing of AI applications.
• Proven ability to work directly with business teams to translate business requirements into technological solutions.
• Strong problem-solving abilities, coupled with excellent communication and interpersonal skills.
• A collaborative mindset, capable of working across diverse teams to drive innovative solutions.

What You'll Do As a Gen AI Solution Architect:

• Partner with business groups across our organization to understand their objectives, use cases, and challenges, and develop innovative, scalable Generative AI applications and solutions to address their needs.
• Lead the discovery of AI use cases and evaluate them for technical feasibility, business impact, and associated risks.
• Architect end-to-end Generative AI solutions, including model selection, training strategies, and deployment architecture, ensuring scalability, performance, and ethical considerations.
• Design, develop, and deliver Generative AI applications using a variety of models, tools, and frameworks.
• Optimize queries and validate the functionality and performance of Generative AI applications through testing and iterative improvement.
• Evaluate and assess new generative AI technologies, including Large Language Models (LLMs), chatbots, vector databases, and Retrieval-Augmented Generation (RAG) architectures.
• Lead proof of concept (PoC) and pilot implementations to validate the potential of Generative AI solutions.
• Provide strategic guidance to ensure AI solutions are aligned with business goals and industry best practices