AWS Cognitive Engineer (Cloud & AI Developer)

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 Bachelor’s 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 Originally posted on Himalayas