AI Architect

Location: Mount Laurel, NJ – Hybrid Onsite
Type: Contract

About the role

We are seeking an experienced AI Architect to lead the design, architecture, and implementation of enterprise-grade Artificial Intelligence solutions. Define AI strategy, build scalable AI/ML platforms, and work closely with business stakeholders, data scientists, engineers, and cloud teams to deliver innovative AI-powered products. The role requires expertise in Generative AI, Machine Learning, Large Language Models (LLMs), cloud AI services, and modern data architectures.

Responsibilities

• Define enterprise AI architecture, technology roadmap, and best practices.
• Design scalable AI/ML and Generative AI solutions aligned with business objectives.
• Architect end-to-end AI systems, including data ingestion, model training, deployment, monitoring, and governance.
• Lead the implementation of LLM-based applications using Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering techniques.
• Evaluate and integrate foundation models, vector databases, and AI frameworks.
• Design secure, scalable, and high-performing AI platforms on cloud environments.
• Collaborate with data engineering, application development, security, and DevOps teams.
• Establish AI governance, responsible AI practices, model lifecycle management, and compliance standards.
• Optimize AI solutions for performance, scalability, cost, and reliability.
• Mentor technical teams and provide architectural guidance across AI initiatives.

Requirements

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• 10+ years of experience in software engineering, data engineering, or AI/ML, with significant experience in solution or enterprise architecture.
• Strong knowledge of Machine Learning, Deep Learning, NLP, and Generative AI.
• Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, embeddings, vector databases, and prompt engineering.
• Experience with Python and AI frameworks such as TensorFlow, PyTorch, LangChain, LlamaIndex, Hugging Face, or similar.
• Experience deploying AI workloads on AWS, Microsoft Azure, or Google Cloud Platform.
• Knowledge of MLOps, CI/CD, containerization (Docker), Kubernetes, and model deployment strategies.
• Experience with data engineering technologies, APIs, and distributed systems.
• Strong understanding of AI security, governance, privacy, and ethical AI principles.
• Excellent communication, stakeholder management, and leadership skills.