AI Solutions Architect

SUMMARY:
AI Solutions Architect

POSITION INFO:
Role:
Our client seeks to appoint an AI Solutions Architect to design and implement AI-driven solutions that align with business objectives. Reporting to the ICT Program Manager, this position will collaborate with cross-functional teams to develop AI strategies, integrating AI technologies into enterprise systems, and ensuring scalability, security, and efficiency.
 
Minimum Qualifications

• An appropriate, recognised qualification at NǪF Level 7, with preference for a qualification in Information Technology, Computer Science, Computer Systems or equivalent.
• Solutions Architecture certification, Scaled Agile Framework, Azure, Google, Oracle, or AWS cloud architecture certification.
• A relevant NǪF level 8 qualification will be an advantage.

• Eight years’ relevant work experience.
• Strong expertise in AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn, etc.) will be an
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• Understanding data architecture, APIs, and microservices will be an advantage.
• Knowledge of DevOps/MLOps practices for AI model deployment will be an advantage.

• AI and Machine Learning.
• Architecture Design.
• Cloud architecture.
• Cloud Computing.
• Code Ǫuality Management.
• Cybersecurity architecture for applications.
• Data Management and Design.
• Database and data warehouse design.
• DevOps and CI/CD.
• Governance and compliance.
• JavaScript programing.
• Net programing.
• Programming and Scripting.
• Python programing.
• Software Development Lifecycle (SDLC).
• SǪL scripting.
• Stakeholder communication.
• Technical problem solving.
• Tool proficiency.
• Business acumen.
• Resilience, attention to detail and sound judgement.

• Design and Implement AI driven Architectures.
• Develop AI Road maps aligned with organisational strategy.
• Assess and recommend AI technologies, tools, and platforms.
• Build and deploy AI/ML models ensuring scalability and performance.
• Integrate AI solutions with new, existing enterprise applications and data pipelines.
• Work with data specialists and developers to optimize data processing and model training workflows.
• Implement change requests on existing applications.
• Oversee model deployment using cloud services and on-premises environments.
• Adhere to clean code principles and maintainable design patterns.
• Resolve identified risks and issues.
• Work closely with software engineers, data stewards and Business Analysts.
• Provide technical guidance and mentorship to the development AI teams.
• Collaborate with Stakeholders to define AI-driven business use cases.
• Advocate for best practices in AI ethics, security, and compliance.
• Stay updated on emerging AI technologies.
• Conduct feasibility studies on new AI applications and enhancements.
• Drive the adoption of responsible and ethical AI practices.