AI ARCHITECT @ NORTHITE
We are seeking a highly skilled AI Architect for a critical on-site role based in Miami, FL, with a minimum project duration of six months. The successful candidate will take a lead role in the design and implementation of enterprise-level AI solutions, focusing specifically on Retrieval-Augmented Generation (RAG) systems, vector search mechanisms, and knowledge platforms powered by Large Language Models (LLMs). This position requires a strategic thinker who can bridge the gap between complex machine learning models and practical business applications.
Candidates will be expected to demonstrate mastery over unstructured data processing, natural language processing, and document AI. The role involves building robust data pipelines and ensuring that all systems are architected with security-by-design principles. Ideally, you will have a background in financial services, particularly in areas like commercial real estate credit or asset management, providing you with the necessary context to navigate complex industry data and compliance requirements.
Candidates will be expected to demonstrate mastery over unstructured data processing, natural language processing, and document AI. The role involves building robust data pipelines and ensuring that all systems are architected with security-by-design principles. Ideally, you will have a background in financial services, particularly in areas like commercial real estate credit or asset management, providing you with the necessary context to navigate complex industry data and compliance requirements.
Key Requirements
10–15 years of professional experience in AI, ML, or enterprise architecture roles.
Proven track record architecting RAG systems, vector search, and LLM-based knowledge platforms.
Strong hands-on programming experience with Python.
Deep expertise with Cloud ML platforms, specifically Microsoft Azure.
Hands-on experience with Vector Databases such as Pinecone or DB Vector.
Proficiency with orchestration frameworks like LangChain or LlamaIndex.
Experience in fine-tuning models and working with embeddings for AI applications.
Familiarity with document chunking, knowledge graphs, and vectorization processes.
Expertise in document AI, NLP, and processing unstructured data sets.
Strong architectural skills across data pipelines and event-driven systems.
Experience with containerization using Docker and Kubernetes (K8s).
Demonstrated ability to implement security-by-design in enterprise architectures.