AI Architect Generative AI

Role: AI Architect Generative AI
Location: Tampa FL (3 Days onsite/week)

Job Description:
Role focused on designing implementing and scaling enterprise-grade AI and Generative AI solutions.

Role Overview
The AI Architect Generative AI will be responsible for defining the technical vision architecture and delivery approach for scalable AI solutions across enterprise environments. The role will focus on large language models Retrieval-Augmented Generation agentic AI frameworks cloud-native AI platforms MLOps/LLMOps governance security and responsible AI adoption. The ideal candidate will work closely with business stakeholders data scientists engineering teams product owners and security teams to convert business needs into production-ready AI capabilities.
Key Responsibilities
Design end-to-end AI and Generative AI architectures aligned with business objectives enterprise standards and technology roadmaps.
Architect scalable solutions using large language models Retrieval-Augmented Generation embeddings vector databases prompt engineering fine-tuning and agentic AI patterns.
Define architecture blueprints reusable patterns solution accelerators and reference implementations for enterprise AI adoption.
Lead technical evaluation and selection of AI platforms model providers orchestration frameworks vector stores cloud services and integration technologies.
Design and operationalize LLMOps and MLOps pipelines covering model evaluation prompt lifecycle management monitoring feedback loops versioning deployment automation and continuous improvement.
Collaborate with data engineering teams to design ingestion indexing chunking embedding semantic search and knowledge retrieval pipelines.
Ensure AI solutions are secure reliable scalable observable cost-effective and compliant with enterprise governance and responsible AI standards.
Define guardrails for responsible AI usage including data privacy bias mitigation explainability auditability human-in-the-loop controls and prompt injection protection.
Provide technical leadership to AI engineers data scientists cloud engineers and application development teams during design build testing and production rollout.
Translate complex AI concepts into clear recommendations for business leaders and non-technical stakeholders.
Stay current with emerging AI technologies frameworks model capabilities risks and industry best practices.