Job Title: AI Architect 

Location: Plano,TX

Duration: 12 Months 

Bill Rate: $77/hour (C2C)

Job Type: W-2, 1099, C2C

Client: To Be Discussed Later

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD,Other

Job Description:

We are seeking an experienced AI Architect with 15+ years of overall technology experience to lead the design, architecture, and implementation of enterprise-scale Artificial Intelligence solutions. The ideal candidate will have deep expertise in Generative AI, Large Language Models (LLMs), Agentic AI, Machine Learning, cloud-native architectures, and enterprise application integration.

The AI Architect will define the organization's AI strategy, establish scalable and secure AI architectures, and lead the development of intelligent applications that solve complex business problems. This individual will work closely with business stakeholders, data scientists, engineering teams, and technology leadership to translate business requirements into robust AI-driven solutions.

The ideal candidate must possess strong hands-on technical expertise, architecture leadership capabilities, and experience delivering production-grade AI solutions across enterprise environments.

• Define and lead enterprise AI architecture strategies, roadmaps, and implementation standards aligned with business objectives.

• Design and architect scalable, secure, and high-performance AI/ML and Generative AI solutions for enterprise applications.

• Lead the architecture and implementation of LLM-based applications, including Retrieval-Augmented Generation (RAG), prompt engineering, embeddings, vector databases, and semantic search.

• Design and implement Agentic AI solutions, including autonomous agents, multi-agent systems, tool calling, orchestration, planning, and workflow automation.

• Evaluate and select appropriate foundation models, LLM platforms, AI frameworks, and technologies based on business and technical requirements.

• Architect AI-powered applications using frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, and other relevant technologies.

• Define enterprise integration patterns connecting AI solutions with APIs, microservices, databases, enterprise applications, and external systems.

• Design cloud-based AI architectures using AWS, Microsoft Azure, or Google Cloud Platform.

• Establish AI governance, responsible AI, security, privacy, compliance, and model risk management practices.

• Design solutions addressing LLM security risks, including prompt injection, data leakage, model misuse, hallucinations, and unauthorized access.

• Establish MLOps and LLMOps practices covering model deployment, monitoring, evaluation, versioning, performance optimization, and continuous improvement.

• Define architecture standards for model observability, tracing, logging, latency management, scalability, and cost optimization.

• Collaborate with data engineering, machine learning, DevOps, application development, cybersecurity, and enterprise architecture teams.

• Lead architecture reviews, technical design discussions, proof-of-concepts, and technology evaluations.

• Provide technical leadership and mentorship to AI engineers, ML engineers, data scientists, and development teams.

• Drive the transition of AI/ML prototypes and proof-of-concepts into reliable, production-ready enterprise solutions.

• Stay current with emerging AI technologies and recommend innovative approaches that deliver measurable business value.