AWS Cognitive Engineer

Role Overview
Our client a leading technology-driven organization is seeking an experienced AWS Cognitive Engineer to design and deliver cloud-native applications enhanced with artificial intelligence capabilities.

In this role you will be responsible for developing scalable secure and intelligent solutions on AWS working closely with cross-functional teams to translate business needs into technical implementations. You will also play a key role in optimizing application performance enhancing AI models and ensuring adherence to best practices in cloud and responsible AI.



Key Responsibilities

• Act as a subject matter expert in AWS cloud services and AI/ML technologies
  
• Partner with cross-functional teams to define architecture and drive key technical decisions
  
• Design and implement AI-powered features using AWS AI/ML services
  
• Build and deploy applications using serverless and microservices-based architectures
  
• Promote best practices and support knowledge sharing within the team
  
• Monitor application and model performance and implement improvements for scalability and accuracy
  
• Ensure solutions align with security governance and responsible AI standards
  
• Contribute to project planning timelines and successful delivery of milestones
  

Qualifications

• Bachelors degree in Computer Science Information Technology Engineering or a related field
  
• Minimum of 3 years of hands-on experience working with AWS services
  
• At least 1 year of experience in AI/ML projects or exposure to AWS AI services is preferred
  
• Relevant AWS certifications (e.g. Solutions Architect or Machine Learning Specialty) are an advantage
  
• Strong analytical thinking and problem-solving skills
  
• Effective communication and collaboration abilities
  
• Ability to lead technical discussions and support team development
  

Technical Skills

• Strong expertise in core AWS services such as compute storage serverless databases and identity management
  
• Solid understanding of cloud architecture and distributed systems
  
• Experience working with AWS AI/ML services (e.g. model development natural language processing image recognition)
  
• Familiarity with generative AI concepts and prompt engineering techniques
  
• Knowledge of MLOps practices including model deployment and monitoring
  
• Experience with serverless frameworks and container technologies (e.g. Docker Kubernetes)
  
• Proficiency in Python or similar programming languages for AI and backend development
  
• Understanding of security best practices in cloud and AI environments