AI Architect-Generative AI & Large Language Models

Orion Innovation•Montvale, NJ

20h•Onsite

About The Position

Orion Innovation is a premier, award-winning, global business and technology services firm. Orion delivers game-changing business transformation and product development rooted in digital strategy, experience design, and engineering, with a unique combination of agility, scale, and maturity. We work with a wide range of clients across many industries including financial services, professional services, telecommunications and media, consumer products, automotive, industrial automation, professional sports and entertainment, life sciences, ecommerce, and education. We are seeking an AI Architect specializing in Generative AI and Large Language Models (LLMs) to help design, deploy, and scale AI solutions for enterprise clients. This role requires deep expertise in machine learning and data science, particularly in the design, evaluation, and operationalization of modern language models and generative AI systems. The AI Architect will work closely with engineering teams and client stakeholders to translate cutting-edge AI capabilities into reliable production systems, while ensuring governance, transparency, and responsible AI practices. The ideal candidate combines technical depth, research awareness, and strong communication skills, enabling them to represent our company confidently in front of senior client stakeholders.

Requirements

Master’s degree in Data Science, Machine Learning, Computer Science, or related field.
Strong expertise in machine learning fundamentals and modern generative AI technologies.
Proven experience designing and deploying AI/ML systems in production environments.
Deep knowledge of:
Large Language Models
Generative AI architectures
ML pipelines and model lifecycle management
Experience working with AI frameworks and ecosystems used for building GenAI applications.
Experience implementing AI governance, explainability, and responsible AI practices.
Strong understanding of enterprise software architecture and distributed systems.

Nice To Haves

Experience with agentic AI systems and orchestration frameworks.
Experience building RAG-based AI systems.
Familiarity with AI platform engineering and scalable AI infrastructure.
Contributions to AI research, open-source projects, or technical publications.
Experience working with enterprise clients in regulated industries.

Responsibilities

AI Architecture & Solution Design
Design and architect enterprise-grade AI solutions leveraging Generative AI and Large Language Models.
Define architecture for LLM-based systems, agentic workflows, retrieval-augmented generation (RAG), and AI copilots.
Evaluate and select appropriate models, frameworks, and infrastructure for production AI systems.
Ensure scalability, reliability, and performance of deployed AI solutions.
Machine Learning & Model Expertise
Provide deep technical expertise in:
Large Language Models (LLMs)
Transformer architectures
Generative AI techniques
Model evaluation and benchmarking
Design approaches for fine-tuning, prompt engineering, and model adaptation.
Guide teams on best practices in ML pipelines, experimentation, and model lifecycle management.
Production Deployment & MLOps
Lead deployment of machine learning and GenAI systems into production environments.
Architect and implement MLOps pipelines, model monitoring, and continuous improvement processes.
Ensure AI systems are secure, scalable, and operationally maintainable.
AI Governance & Responsible AI
Implement frameworks for:
AI governance
Model explainability
Transparency
Risk management
Ensure compliance with enterprise AI governance standards and regulatory expectations.
Define policies for model validation, bias mitigation, and responsible deployment.
Client Engagement & Technical Leadership
Act as a trusted technical advisor to client stakeholders.
Clearly communicate complex AI concepts to executives, architects, and engineering teams.
Represent the company with credibility in technical and strategic discussions around AI adoption.
Work closely with client teams to translate business problems into AI-driven solutions.
Research & Innovation
Stay current with emerging developments in:
Generative AI
Large language models
AI agents and agentic architectures
AI infrastructure and tooling
Evaluate new research and technologies to determine their practical applicability in enterprise environments.
Help shape the organization’s AI strategy and technical direction.