Title: Gen AI Architect
Location: Charlotte NC (Need Onsite day 1 hybrid 3 days from office).
Duration: 12 months
Position type: W2 contract
Job Description:
The Gen AI Architect will leverage advanced Generative AI models and Azure OpenAI services to develop innovative solutions for investment banking processes.
The ideal candidate will have a strong background in investment banking hands-on experience with Microsoft Azure OpenAI and expertise in Retrieval-Augmented Generation (RAG).
Responsibilities:
-
Define and drive the AI/ML architecture and roadmap including both traditional machine learning and Generative AI (GenAI) use cases.
-
Design comprehensive end-to-end AI solutions covering data ingestion feature engineering model training inference pipelines and monitoring frameworks.
-
Lead the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks utilizing tools such as LangChain LangGraph or similar.
-
Collaborate with business stakeholders to translate requirements into scalable AI-driven technical solutions.
-
Evaluate and select appropriate AI/ML tools cloud services frameworks and libraries based on use case needs and industry best practices.
-
Ensure models adhere to governance security explainability and regulatory compliance embedding ethical AI principles into system design.
-
Guide engineering teams in the implementation of AI components emphasizing scalability reliability and performance optimization.
-
Partner with DevOps teams to establish CI/CD pipelines for AI including model versioning deployment automation and ongoing A/B testing.
-
Keep abreast of the latest industry research breakthroughs and emerging trends in AI recommending adoption of best practices and innovative solutions.
Requirements:
-
Proven experience 10 years excel in leading AI/ML architecture and strategy in enterprise environments.
-
Strong expertise in designing and deploying large-scale AI/ML solutions including LLMs and RAG frameworks.
-
Experience with AI/ML tools and frameworks such as TensorFlow PyTorch Hugging Face LangChain LangGraph or similar.
-
Deep understanding of data workflows feature engineering model training evaluation and deployment.
-
Knowledge of cloud platforms (AWS Azure GCP) and services tailored for AI deployment.
-
Familiarity with model governance security explainability and ethical AI standards.
-
Experience in developing CI/CD pipelines for AI/ML including model versioning monitoring and performance tuning.
-
Strong problem-solving communication and stakeholder management skills.
Preferred but not required:
-
Advanced degree (Ph.D. Master s) in Computer Science Data Science AI or related fields.
-
Publications or practical contributions to AI research and open-source projects.
-
Experience working in regulated industries or environments requiring compliance and governance.
-
Familiar with project management and Agile practices.
Title: Gen AI Architect Location: Charlotte NC (Need Onsite day 1 hybrid 3 days from office). Duration: 12 months Position type: W2 contract Job Description: The Gen AI Architect will leverage advanced Generative AI models and Azure OpenAI services to develop innovative solutions for investment...
Title: Gen AI Architect
Location: Charlotte NC (Need Onsite day 1 hybrid 3 days from office).
Duration: 12 months
Position type: W2 contract
Job Description:
The Gen AI Architect will leverage advanced Generative AI models and Azure OpenAI services to develop innovative solutions for investment banking processes.
The ideal candidate will have a strong background in investment banking hands-on experience with Microsoft Azure OpenAI and expertise in Retrieval-Augmented Generation (RAG).
Responsibilities:
-
Define and drive the AI/ML architecture and roadmap including both traditional machine learning and Generative AI (GenAI) use cases.
-
Design comprehensive end-to-end AI solutions covering data ingestion feature engineering model training inference pipelines and monitoring frameworks.
-
Lead the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) frameworks utilizing tools such as LangChain LangGraph or similar.
-
Collaborate with business stakeholders to translate requirements into scalable AI-driven technical solutions.
-
Evaluate and select appropriate AI/ML tools cloud services frameworks and libraries based on use case needs and industry best practices.
-
Ensure models adhere to governance security explainability and regulatory compliance embedding ethical AI principles into system design.
-
Guide engineering teams in the implementation of AI components emphasizing scalability reliability and performance optimization.
-
Partner with DevOps teams to establish CI/CD pipelines for AI including model versioning deployment automation and ongoing A/B testing.
-
Keep abreast of the latest industry research breakthroughs and emerging trends in AI recommending adoption of best practices and innovative solutions.
Requirements:
-
Proven experience 10 years excel in leading AI/ML architecture and strategy in enterprise environments.
-
Strong expertise in designing and deploying large-scale AI/ML solutions including LLMs and RAG frameworks.
-
Experience with AI/ML tools and frameworks such as TensorFlow PyTorch Hugging Face LangChain LangGraph or similar.
-
Deep understanding of data workflows feature engineering model training evaluation and deployment.
-
Knowledge of cloud platforms (AWS Azure GCP) and services tailored for AI deployment.
-
Familiarity with model governance security explainability and ethical AI standards.
-
Experience in developing CI/CD pipelines for AI/ML including model versioning monitoring and performance tuning.
-
Strong problem-solving communication and stakeholder management skills.
Preferred but not required:
-
Advanced degree (Ph.D. Master s) in Computer Science Data Science AI or related fields.
-
Publications or practical contributions to AI research and open-source projects.
-
Experience working in regulated industries or environments requiring compliance and governance.
-
Familiar with project management and Agile practices.
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