Full-Stack AI Engineer — AWS AI

About the role

We are seeking a highly motivated and technically strong Full-Stack AI Engineer - AWS AI to join our team. This individual will play a key role in designing, developing, deploying, and supporting enterprise-grade AI applications leveraging AWS AI services, Large Language Models (LLMs), agentic AI frameworks, APIs, cloud-native architectures, and modern web technologies.

Key Responsibilities

• AI Application Development
• Design, develop, and maintain AI-powered applications using AWS AI and Machine Learning services.
• Build scalable enterprise solutions utilizing Generative AI, Retrieval-Augmented Generation (RAG), intelligent workflows, and AI agents.
• Implement AI-enabled business solutions that enhance operational efficiency and customer experiences.
• Collaborate with business teams to translate AI use cases into production-ready applications.

Full-Stack Engineering

• Develop front-end and back-end components of AI-driven applications.
• Build responsive user interfaces and APIs supporting AI-powered experiences.
• Design reusable and scalable application architectures.
• Develop secure, maintainable, and performant code following industry best practices.
• Support integration of AI services into enterprise web applications and business platforms.

AWS AI & Cloud Engineering

• Agentic AI Solutions
• API & Enterprise Integrations

Required Qualifications

• Education: Bachelor's degree in Computer Science, Engineering, Information Technology, or related field. Equivalent practical experience may be considered.
• Experience: 3-5 years of hands-on software engineering experience. Experience building and deploying cloud-native applications. Experience working on AI, machine learning, or Generative AI projects. Experience supporting production enterprise applications.

Information Security Responsibilities

• Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols.
• Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets.
• Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.).
• Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information.