Senior AI Architect – Onsite in Charlotte, NC

Senior AI Architect – Onsite in Charlotte, NC

Location: Charlotte, NC

Work Arrangement: Onsite five days per week

Employment Type: Direct W-2 employment with Trilogy Next Gen

Duration: Long-term contract engagement

C2C: Not available

Visa Status: No specific visa restrictions; candidates must be eligible for direct W-2 employment with Trilogy Next Gen

Trilogy Next Gen is seeking an experienced Senior AI Architect to support one of our long-standing banking customers in Charlotte, North Carolina.

This is a hands-on architecture and technical leadership role focused on designing and implementing enterprise AI and Generative AI solutions. The ideal candidate will have deep experience across AI/ML architecture, Large Language Models, cloud-based AI platforms, data engineering, model integration, security, governance, and enterprise application architecture.

The selected architect will work closely with business stakeholders, application teams, data teams, security, infrastructure, and engineering leadership to define scalable and production-ready AI solutions for a large financial-services environment.

This is a long-term engagement with an established Trilogy Next Gen customer and requires working onsite in Charlotte, NC, five days per week
.

The selected candidate must be a direct W-2 employee of Trilogy Next Gen
. We will not respond to or entertain C2C, third-party consulting, subcontracting, or agency submissions.

• Define enterprise architecture for AI, machine learning, and Generative AI solutions.
• Design scalable, secure, and production-ready AI platforms and application architectures.
• Lead architecture for solutions leveraging Large Language Models and other foundation models.
• Design and implement Retrieval-Augmented Generation (RAG) architectures.
• Define strategies for model selection, prompt engineering, embeddings, vector search, and model orchestration.
• Architect integration between AI solutions and enterprise applications, APIs, data platforms, and business workflows.
• Evaluate and recommend AI platforms, frameworks, tools, and architectural patterns.
• Design solutions using cloud-native AI and machine-learning services.
• Partner with data architects and engineers to establish appropriate data pipelines and data-access patterns for AI workloads.
• Define architectural standards for model lifecycle management, monitoring, observability, and performance.
• Establish patterns for responsible AI, security, privacy, governance, and regulatory compliance.
• Design mechanisms to protect sensitive enterprise and customer data when interacting with AI models.
• Lead technical discussions and architecture reviews with engineering, infrastructure, cybersecurity, and business teams.
• Develop reference architectures, solution diagrams, technical standards, and reusable AI patterns.
• Provide technical leadership and mentorship to engineering and development teams.
• Support proof-of-concept efforts and guide successful solutions into enterprise production environments.

• 10+ years of enterprise technology experience with significant experience in architecture or technical leadership.
• Strong hands-on experience designing AI and machine-learning architectures
  .
• Experience architecting and implementing Generative AI and Large Language Model solutions
  .
• Strong understanding of LLM concepts including prompting, embeddings, context management, tokenization, and model inference.
• Experience designing Retrieval-Augmented Generation (RAG) solutions.
• Experience with vector databases or vector-search technologies.
• Experience integrating AI models with enterprise applications and APIs.
• Strong understanding of AI/ML lifecycle management, model deployment, monitoring, and observability.
• Experience with Python and common AI/ML development frameworks.
• Strong experience with at least one major cloud platform such as AWS, Azure, or Google Cloud.
• Experience with cloud-based AI and machine-learning services.
• Strong understanding of data architecture, data engineering, and enterprise data integration.
• Experience with REST APIs, microservices, event-driven architectures, and distributed systems.
• Understanding of…