As a Gen AI Architect, your primary role will be to design and develop advanced artificial intelligence solutions for various applications. You will work closely with cross-functional teams to understand business requirements and translate them into scalable and efficient AI architecture. You will also be responsible for leading the implementation and deployment of AI models and systems.

Responsibilities:

• Lead the design of architecture for generative AI solutions within the Azure ecosystem. Collaborate with project managers, data scientists, software engineers, and other stakeholders to understand business goals and determine AI requirements.
• Design and develop AI architectures, frameworks, and algorithms that can support large-scale and complex AI solutions.
• Evaluate and select appropriate AI technologies, tools, and frameworks to achieve desired performance, accuracy, and scalability.
• Lead the development and implementation of AI models, ensuring adherence to best practices in machine learning and deep learning.
• Develop and maintain AI pipelines, incorporating data cleaning, pre-processing, feature engineering, model training, and validation processes.
• Optimize AI models and systems for performance, scalability, and efficiency.
• Conduct regular code reviews and provide technical guidance to junior members of the team.
• Stay up-to-date with the latest advancements in AI technologies, frameworks, and algorithms, and identify opportunities for their application in the organization.
• Collaborate with infrastructure teams to ensure smooth deployment and monitoring of AI models in production environments.
• Document AI architectures, design decisions, and technical specifications for reference and knowledge sharing.

Skills:

Primary Skills:

• Generative AI Expertise: Extensive experience in designing and implementing generative AI solutions, including knowledge of various generative models such as GANs, VAEs, and autoregressive models. Ability to apply generative AI techniques to diverse use cases such as image generation, text generation, and creative content synthesis.
• Azure Proficiency: Profound understanding and hands-on experience with Azure cloud services relevant to AI, including Azure Machine Learning, Azure Cognitive Services, Azure Databricks, and Azure Kubernetes Service (AKS). Ability to leverage Azure's capabilities to architect end-to-end AI solutions and optimize performance.
• Architecture Design: Strong architectural skills with the ability to design scalable, reliable, and cost-effective architectures for AI solutions. Proficiency in designing distributed systems, microservices architectures, and containerized solutions using technologies such as Docker and Kubernetes.
• Leadership and Collaboration: Exceptional leadership skills with the ability to lead cross-functional teams and drive architectural decisions. Proven experience in mentoring junior team members, conducting code reviews, and fostering a culture of innovation and collaboration.
• Problem-solving and Innovation: Strong analytical and problem-solving skills, with a track record of proposing innovative solutions to complex technical challenges. Ability to stay updated on emerging AI technologies, best practices, and industry trends to drive continuous improvement.

Secondary Skills:

• Security and Compliance: Understanding of security principles and best practices in AI development, with the ability to implement security controls, encryption mechanisms, and access management policies to protect AI models and sensitive data. Familiarity with regulatory compliance standards such as GDPR, HIPAA, and industry-specific regulations.
• Integration and Deployment: Proficiency in implementing CI/CD pipelines, automation scripts, and infrastructure as code (IaC) using tools such as Azure DevOps, Terraform, or Ansible. Experience in containerization and orchestration of AI workloads using Docker and Kubernetes.
• Software Development: Strong programming skills in languages such as Python, with experience in developing AI applications, RESTful APIs, and microservices architectures. Familiarity with software development methodologies such as Agile or Scrum.
• Communication and Presentation: Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders. Experience in preparing and delivering technical presentations, architecture diagrams, and documentation to communicate architectural decisions and design rationale effectively.