AI Architect - R01570927

Brillio•Edison, NJ

3d•Hybrid

About The Position

Brillio is seeking an AI Architect to join their team in Plainsboro, NJ. This is a hybrid role requiring a minimum of 3-4 days onsite per week. The AI Architect will be responsible for leveraging expertise in Data Science, Machine Learning, and Artificial Intelligence to solve business problems. The role involves hands-on experience in data analysis, feature engineering, model development, evaluation, and deployment of machine learning solutions. A good understanding of Generative AI concepts, including LLMs, prompt engineering, RAG, AI agents, and emerging AI frameworks like MCP, is essential. The candidate will work with structured and unstructured data, build scalable AI/ML solutions, and collaborate with cross-functional teams to achieve data-driven outcomes. Strong problem-solving, analytical, and communication skills are required, along with a willingness to learn new technologies and AI/ML trends.

Requirements

Experience in Data Science, Machine Learning, Artificial Intelligence, or related fields.
Strong proficiency in SQL and Python.
Hands-on experience in data analysis, feature engineering, model development, evaluation, and deployment of machine learning solutions to solve business problems.
Good understanding of Generative AI concepts, including Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), AI agents, and emerging AI frameworks and protocols such as MCP.
Ability to work with structured and unstructured data.
Ability to build scalable AI/ML solutions.
Ability to collaborate with cross-functional teams to translate business requirements into data-driven outcomes.
Strong problem-solving, analytical, and communication skills.
Demonstrated willingness and enthusiasm to learn new technologies, tools, and emerging AI/ML trends in a fast-evolving landscape.

Nice To Haves

Experience with Snowflake data platform.
Exposure to Snowflake AI capabilities and Cortex services.
Familiarity with MLOps, model deployment, monitoring, and AI application lifecycle management.
Knowledge of data warehousing, data engineering concepts, and API integrations.
Exposure to GenAI application development, vector databases, semantic search, and AI orchestration frameworks.
Lifesciences experience.

Responsibilities

Leverage expertise in Data Science, Machine Learning, and Artificial Intelligence to solve business problems.
Perform hands-on data analysis, feature engineering, model development, evaluation, and deployment of machine learning solutions.
Apply knowledge of Generative AI concepts, including LLMs, prompt engineering, RAG, AI agents, and emerging AI frameworks such as MCP.
Work with structured and unstructured data to build scalable AI/ML solutions.
Collaborate with cross-functional teams to translate business requirements into data-driven outcomes.
Utilize strong problem-solving, analytical, and communication skills.
Demonstrate a willingness and enthusiasm to learn new technologies, tools, and emerging AI/ML trends.