AI Architect

Description

Client

Client

Location

Charlotte, NC & iselin, NJ (Need local candidate who can be available to work in Hybrid model)

Day-to-Day Job Duties

Design and lead AI/Generative AI architectures for enterprise applications and business solutions.

Define AI strategy, reference architectures, technology standards, and implementation roadmaps.

Design solutions using LLMs, Generative AI, RAG, AI agents, prompt engineering, and AI/ML services.

Evaluate and select AI models, platforms, frameworks, and cloud services based on business and technical requirements.

Design secure and scalable AI solutions across AWS, Azure, or GCP.

Integrate AI capabilities with enterprise applications, APIs, databases, and data platforms.

Design RAG pipelines, vector databases, embeddings, document processing, and knowledge retrieval solutions.

Establish AI security, governance, responsible AI, data privacy, and model-risk controls.

Collaborate with business stakeholders, data scientists, ML engineers, software engineers, architects, and DevOps teams.

Lead PoCs and prototypes and guide solutions from architecture through production implementation.

Define AI solution performance, scalability, reliability, cost, and monitoring requirements.

Provide technical leadership and mentor development teams on AI architecture and implementation.

Basic Qualifications

10+ years of experience in software architecture, technology architecture, or solution architecture.

5+ years of experience designing AI/ML or advanced analytics solutions.

3+ years of experience with Generative AI and LLM-based solutions.

3+ years of experience with cloud platforms such as AWS, Azure, or GCP.

3+ years of experience with Python and AI/ML development frameworks.

2+ years of experience designing RAG, vector search, embeddings, and knowledge-retrieval solutions.

2+ years of experience integrating AI/LLM services through REST APIs or enterprise applications.

2+ years of experience with AI security, governance, data privacy, and responsible AI practices.

3+ years of experience with enterprise application integration, APIs, databases, and distributed systems.

2+ years of experience leading AI PoCs, prototypes, or production implementations.

3+ years of experience working with cross-functional engineering, data, product, and business teams.

Education

Bachelor’s degree in computer science, Engineering, Artificial Intelligence, Data Science, or a related field.

Nice to Have

2+ years of experience with AI agents and agentic workflows.

Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, OpenAI, or Anthropic.

Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.

Experience with vector databases such as Pinecone, Azure AI Search, OpenSearch, or similar technologies.

Experience with MLOps/LLMOps, model monitoring, evaluation, and AI observability.

Experience in financial services, insurance, or other regulated industries.

Experience implementing enterprise-scale AI modernization initiatives.