Gen-AI Architect

1. Job Purpose
To design and implement Generative AI solutions that align with business objectives and drive innovation. The Gen-AI Architect will leverage advanced AI technologies and frameworks to develop scalable and efficient models, ensuring optimal performance and integration within existing systems.

2. Key Responsibilities
Architecture Design:

Design robust and scalable architectures for Generative AI applications.
Define best practices for model development, deployment, and maintenance.
Technology Selection:

Evaluate and select appropriate AI technologies and frameworks (e.g., TensorFlow, PyTorch, OpenAI GPT, etc.) for specific use cases.
Stay current with emerging technologies in the AI landscape.
Model Development:

Oversee the development of Generative AI models, ensuring they meet quality and performance standards.
Collaborate with data scientists and engineers to optimize model training and deployment.
Integration:

Ensure seamless integration of AI solutions with existing systems and workflows.
Collaborate with software development teams to implement AI capabilities in applications.
Documentation and Standards:

Create and maintain architectural documentation, including design specifications and technical guidelines.
Establish coding and documentation standards for AI development.
Mentorship and Training:

Provide technical leadership and mentorship to team members on Generative AI practices.
Conduct training sessions and workshops to share knowledge and best practices.
3. Qualifications
Education:

Bachelor s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. A Master s degree is preferred.
Experience:

Minimum of [X years] of experience in AI architecture and implementation, specifically with Generative AI technologies.
Proven track record of delivering successful AI projects from conception to deployment.
Technical Skills:
Gen-AI Architect - Location Remote It can be part time to start and can convert to full time
Strong knowledge of AI frameworks (e.g., TensorFlow, PyTorch, Keras) and Generative AI models (e.g., GANs, VAEs, Transformers).
Proficiency in programming languages commonly used in AI (e.g., Python, R).
Architectural Knowledge:

Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for AI deployment.
Understanding of data engineering, data pipelines, and database technologies.
4. Personal Attributes
Innovative Thinker: Ability to explore new ideas and drive creative solutions.
Collaborative: Strong interpersonal skills to work effectively with cross-functional teams.
Analytical Mindset: Ability to analyze complex problems and design effective architectural solutions.
Continuous Learner: Commitment to staying updated on advancements in AI and related technologies.