JOB SUMMARY

As a Generative AI Architect, you will lead the architecture design and development of Generative AI solutions for multiple business domains and use cases across the enterprise. You will collaborate with cross-functional teams to comprehend business needs and turn them into scalable and effective Generative AI architectures and platforms. You will also lead the execution and delivery of Generative AI projects.
This position will be based onsite at Vertiv’s Westerville, OH - HQ location.

Responsibilities :

• Work in conjunction with business teams, data scientists, software engineers, and other relevant parties to comprehend business objectives and define technical requirements.
• Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
• Develop and implement applications using advanced Generative AI models such as OpenAI GPT 3.5 or 4.0, Anthropic Claude, Google Plam2, Meta Llama2 or Llama3.
• Apply frameworks such as LangChain and Llama Index for efficient indexing, retrieval, and chaining of language models, enhancing the contextual understanding and response generation of applications.
• Assess and choose suitable Generative AI technologies, tools, and frameworks to attain the required performance, precision, and scalability.
• Oversee the fine-tuning and deployment of Large Language Models, ensuring compliance with top-tier practices in Generative AI and machine learning.
• Construct and sustain Generative AI workflows, incorporating stages such as data cleansing, pre-processing, model training or fine-tuning, and feedback loop.
• Evaluate Large Language Models and systems for optimal performance, scalability, and efficiency.
• Conduct frequent code assessments and provide technical mentorship to less experienced team members.
• Stay up to date on the latest trends and progress in Generative AI technologies, frameworks, and algorithms, and pinpoint opportunities for their use within the organization.
• Cooperate with infrastructure teams to guarantee seamless deployment and monitoring of Large Language Models in operational environments.
• Document Generative AI design choices and technical specifications for reference and knowledge dissemination.

Requirements :

• Bachelor’s Degree in Computer Science, Engineering, Mathematics, or related field.
• At least 7 years of experience in artificial intelligence, machine learning, or data science.
• Experience in Generative AI architectures and frameworks such as retrieval augmented generation, vectorization and embeddings, and multi-agent Generative AI architecture solutions.
• Experience working with multiple Large Language Models (e.g., Azure Open AI GPT 3.5/4.0, Meta Llama2 or Llama3, Google Palm2).
• Experience in designing and developing artificial intelligence solutions for various domains, such as natural language processing (NLP), computer vision, speech recognition, deep learning, etc.
• Experience in deploying and monitoring artificial intelligence solutions on cloud environments (AWS and/or Azure)
• Excellent problem-solving and analytical skills, with the ability to break down complex problems into actionable components.
• Strong communication and collaboration skills, with the ability to work effectively within cross-functional teams.
• Strong knowledge of the latest advancements in Generative AI technologies, frameworks, and platforms.
• Knowledge of ethical considerations and responsible Generative AI practices.
• Experience in leading or managing artificial intelligence projects or teams.
• Strong communication and presentation skills, with the ability to explain complex artificial intelligence concepts and insights to technical and non-technical audiences.
• Preferred Requirements :
• Master’s degree or PhD in Artificial Intelligence, Machine Learning, Data Science, or related field
• Proficiency in programming languages such as Python, Java, or C++, and familiarity with popular AI libraries and frameworks (e.g., TensorFlow, PyTorch, Keras)
• Certification or training in artificial intelligence, machine learning, or data science.
• Experience in working with big data technologies, such as Hadoop, Spark, Kafka, etc.

• Experience in working with web or mobile development technologies, such as HTML, CSS, JavaScript, React, Angular, etc.Familiarity with agile or scrum methodologies and project management tools, such as Jira, Trello, etc.

• Work in conjunction with business teams, data scientists, software engineers, and other relevant parties to comprehend business objectives and define technical requirements.
• Architect Generative AI solutions using the latest techniques such as retrieval augmented generation, transformer architectures, etc. to accommodate large-scale and intricate Generative AI solutions.
• Develop and implement applications using advanced Generative AI models such as OpenAI GPT 3.5 or 4.0, Anthropic Claude, Google Plam2, Meta Llama2 or Llama3.
• Apply frameworks such as LangChain and Llama Index for efficient indexing, retrieval, and chaining of language models, enhancing the contextual understanding and response generation of applications.
• Assess and choose suitable Generative AI technologies, tools, and frameworks to attain the required performance, precision, and scalability.
• Oversee the fine-tuning and deployment of Large Language Models, ensuring compliance with top-tier practices in Generative AI and machine learning.
• Construct and sustain Generative AI workflows, incorporating stages such as data cleansing, pre-processing, model training or fine-tuning, and feedback loop.
• Evaluate Large Language Models and systems for optimal performance, scalability, and efficiency.
• Conduct frequent code assessments and provide technical mentorship to less experienced team members.
• Stay up to date on the latest trends and progress in Generative AI technologies, frameworks, and algorithms, and pinpoint opportunities for their use within the organization.
• Cooperate with infrastructure teams to guarantee seamless deployment and monitoring of Large Language Models in operational environments.
• Document Generative AI design choices and technical specifications for reference and knowledge dissemination