Artificial Intelligence Architect – Econet 465 views

Artificial Intelligence Architect x2

Job Description

Job Purpose

The Artificial Intelligence (AI) Architect defines and augments staff and customers’ digital experience by ensuring that AI / Machine Learning (ML) technologies are embedded into business automation and product offerings. Beyond the translation of business needs into architectural designs using AI solutions whilst ensuring all integrations conform to international standards and leading AI technology frameworks and architectures, the AI Architect chooses the right technologies and effectively manages the evolution of the architecture in line with the changing business and customer journeys. The AI Architect is also part of the multidisciplinary AI/ML implementation team, responsible for planning technical implementation, then guiding and approving the AI / ML offering as it is developed. He/she is active in the innovative identification of new revenue and cost-effectiveness opportunities.

Key Responsibilities

• Designs end to end Artificial Intelligent infrastructure architectures, for both On-prem and public cloud to support AI business solutions in line with DSP strategy.
• Builds and maintains platforms that easily convert models into APIs for integrating AI into the overall IT infrastructure.
• Designs AI Frameworks that are agile and repeatable for integrating AI solutions into the enterprise ecosystem,
• Benchmarks and profiles the AI systems/algorithms, APIs and platforms to identify the bottlenecks and manage solution roadmaps.
• Plans the implementation of AI solutions, choosing the right technologies and evaluating the evolution of the architecture to support future needs without much disruption.
• Maintains and optimizes infrastructure hosting the AI solutions, Performs impacts assessment and update all transitional architectures.
• Leads architecture review and approves processes for solution architectures.
• Leads teams to research and develop new ideas and apply AI offerings to complex product challenges across Technology Solutions.
• Oversees and approves the end-to-end development and implementation of the AI innovations in line with DSP Strategy.
• Guides the designs, development, testing and building of MLOPS-as-a-service solutions leveraging On-prem cluster environment.
• Implements and automates continuous integration, continuous delivery, and continuous training for machine learning systems.
• Engages vendors, contractors, service providers and internal stakeholders on support issues for all AI deployments.
• Approves AI solutions that adhere to Enterprise Architecture, Development, and Information Risk Management standards and policies.

Qualification, Skills and Experience

• 6 O Levels Including Mathematics, Science and English.
• 2 A Level passes
• Degree in Computer Science, Engineering, IT, Mathematics, Statistics or equivalent.
• A relevant specialist qualification e.g. MBA / Masters in a relevant Information Technology discipline, Advanced Programming and/or TOGAF will be an added advantage
• 2 to 4 years experience working with data science tools and Frameworks, e.g. TensorFlow/ Keras, PyTorch, sci-kit-learn, OpenCV, or Spacy and in developing on cloud platforms (on AWS, GCP or Azure) in a similar or related environment.
• 2+ years of experience in Business Case Development and Strategic Storytelling is an advantage.
• Experience architecting, designing, building and deploying ML solutions on a highly public cloud or on-prem systems.
• A recognised agile delivery qualification is preferred.