Title: Sr. AI Architect
Location: Charlotte NC
Hybrid 3 days a week from office.
Duration; long term
Position type: W2 contract.
Mandatory skills: AI/ML architecture ML and Generative AI (GenAI) use cases Large Language Models (LLMs) RAG (Retrieval-Augmented Generation) LangChain LangGraphCI/CD for AI pipelines Min experience: 10 Years
Job Description:
- Define and drive the AI/ML architecture and roadmap including traditional ML and Generative AI (GenAI) use cases.
- Design end-to-end AI solutions including data ingestion feature engineering model training inference pipelines and monitoring frameworks.
- Lead the integration of Large Language Models (LLMs) and RAG (Retrieval-Augmented Generation) frameworks using tools such as LangChain LangGraph or similar.
- Collaborate with stakeholders to translate business requirements into AI-driven technical solutions.
- Evaluate and select appropriate AI/ML tools cloud services frameworks and libraries for specific use cases.
- Ensure model governance security explainability and compliance with ethical AI practices and regulatory requirements.
- Guide engineering teams in the implementation of AI components ensuring scalability reliability and performance.
- Work with DevOps teams to enable CI/CD for AI pipelines including model versioning and A/B testing.
- Stay current with industry trends research and advancements in AI and recommend best practices for adoption.
Title: Sr. AI Architect Location: Charlotte NC Hybrid 3 days a week from office. Duration; long term Position type: W2 contract. Mandatory skills: AI/ML architecture ML and Generative AI (GenAI) use cases Large Language Models (LLMs) RAG (Retrieval-Augmented Generation) LangChain LangGraphCI/...
Title: Sr. AI Architect
Location: Charlotte NC
Hybrid 3 days a week from office.
Duration; long term
Position type: W2 contract.
Mandatory skills: AI/ML architecture ML and Generative AI (GenAI) use cases Large Language Models (LLMs) RAG (Retrieval-Augmented Generation) LangChain LangGraphCI/CD for AI pipelines Min experience: 10 Years
Job Description:
- Define and drive the AI/ML architecture and roadmap including traditional ML and Generative AI (GenAI) use cases.
- Design end-to-end AI solutions including data ingestion feature engineering model training inference pipelines and monitoring frameworks.
- Lead the integration of Large Language Models (LLMs) and RAG (Retrieval-Augmented Generation) frameworks using tools such as LangChain LangGraph or similar.
- Collaborate with stakeholders to translate business requirements into AI-driven technical solutions.
- Evaluate and select appropriate AI/ML tools cloud services frameworks and libraries for specific use cases.
- Ensure model governance security explainability and compliance with ethical AI practices and regulatory requirements.
- Guide engineering teams in the implementation of AI components ensuring scalability reliability and performance.
- Work with DevOps teams to enable CI/CD for AI pipelines including model versioning and A/B testing.
- Stay current with industry trends research and advancements in AI and recommend best practices for adoption.
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