ILink Digital - AI Architect

We are seeking a visionary AI Architect to lead the design, development, and implementation of cutting-edge AI solutions. The ideal candidate will have a strong background in machine learning, data engineering, cloud architecture, and enterprise-grade solution design. You will collaborate with stakeholders to translate business challenges into scalable AI-driven systems.

Key Responsibilities

• Lead the design and architecture of AI/ML solutions across the organization.
• Collaborate with data scientists, engineers, product owners, and business leaders to define AI use cases and deliverables.
• Define architecture standards and best practices for AI solution development and deployment.
• Ensure AI models are scalable, robust, and integrated with existing systems and data platforms.
• Oversee end-to-end MLOps processes, including versioning, monitoring, and continuous integration/deployment (CI/CD).
• Evaluate and select AI tools, frameworks, and technologies aligned with enterprise needs.
• Stay current on AI/ML trends, tools, and regulations (including ethical AI practices).
• Provide technical leadership and mentorship to development teams.
• Prepare architecture documentation and presentations for stakeholders and leadership.
  
  

• Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or related field.
• Proven experience in architecting AI/ML solutions in cloud environments (AWS, Azure, or GCP).
• Deep understanding of machine learning algorithms, NLP, computer vision, and deep learning frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
• Strong proficiency in Python and relevant ML libraries.
• Solid experience with data engineering pipelines, data lakes, and APIs.
• Familiarity with MLOps platforms (e.g., MLflow, Kubeflow, SageMaker, Azure ML).
• Strong knowledge of software architecture patterns and microservices.
• Excellent communication, stakeholder management, and documentation skills.
  
  

• AI/ML certification (e.g., Google Professional ML Engineer, AWS Machine Learning Specialty).
• Experience working in regulated industries (healthcare, finance, etc.).
• Familiarity with Generative AI, LLMs (like GPT), and Responsible AI principles.
• Experience in DevOps or Infrastructure as Code (e.g., Terraform, Docker, Kubernetes).