Senior AI Architect

Position Details

Charlotte, NC (Need Onsite day 1, hybrid 3 days from office)

Job Type: W2 contract

Role

Assemble architecture designs
produce clear, end-to-end architecture artifacts: solution designs, reference architectures, diagrams, patterns, and architecture decision records.
Apply AI capabilities design and integrate AI / GenAI / machine-learning components into solutions, and advise on appropriate patterns, tooling, and trade-offs.
Drive rapid prototypes
build quick proofs of concept and working prototypes to validate architecture decisions, de-risk options, and accelerate stakeholder alignment.
Partner across teams
work with engineering, product, and business partners to align architecture with delivery goals and non-functional requirements (security, scalability, resilience, cost).
Document and communicate
present designs and trade-offs clearly to both technical and non-technical audiences, and keep architecture documentation current and usable.
Uphold standards
apply enterprise architecture standards, controls, and best practices throughout design and prototyping.

Requirements

• Demonstrable hands-on AI experience
  practical work building, integrating, or architecting AI / GenAI / ML solutions.
• Proven ability to put architecture details together
  a track record of producing clear, complete architecture designs and documentation.
• Able to drive quick prototypes
  rapidly stand up POCs and working prototypes to test and demonstrate ideas.
• Senior, hands-on technical background
  operating at a Lead Architect level, with strong design fundamentals across modern application, integration, and cloud patterns.
• Strong communication skills
  able to explain architecture and trade-offs to technical teams and business stakeholders alike.
• Self-directed and comfortable working across ambiguity
  to deliver tangible outcomes quickly.

Technical Skills

• Representative technical skills for these roles. Candidates should bring strong depth across several of these areas tailor to our stack as needed:
• AI & Machine Learning
  GenAI and large language models (LLMs), retrieval-augmented generation (RAG), agentic and prompt-engineering patterns, model APIs and integration, embeddings and vector stores; familiarity with common ML frameworks.
• Cloud & Platform
  hands-on experience with at least one major cloud (AWS, Azure, or GCP); containers and orchestration (Docker, Kubernetes); serverless services.
• Architecture & Integration
  microservices, event-driven and API-led design, REST / GraphQL APIs, messaging and streaming (e.g., Kafka), and enterprise integration patterns.
• Data & Information Architecture
  data modeling, relational and NoSQL databases (strong SQL), data lakes / warehouses, ETL / ELT pipelines, and data governance / metadata.
• Languages & Prototyping
  proficiency in Python and/or Java (or comparable); rapid prototyping, scripting, and notebook-based experimentation.
• Engineering Practices
  CI/CD, infrastructure as code (e.g., Terraform), Git-based version control, and automated testing.
• Architecture Tooling
  modeling and diagramming (C4, UML, or ArchiMate) and architecture decision records (ADRs).

Preferred, But Not Required

• Depth in data / information architecture experience
  designing data models, information flows, data platforms, or enterprise information architecture.
• Finance domain experience
  prior work in Finance functions, especially Controllers / financial control and related processes.