Full Stack Engineer

Introduction

This role focuses on developing custom B2B solutions that integrate AI and ML technologies.

It emphasizes expertise in Amazon Web Services (AWS) enterprise deployments and requires hands-on experience with modern cloud architectures and deployment strategies. Compensation is commensurate with experience, and equity options are available. EOE.

Responsibilities

• Design, Develop, and Maintain Full-Stack Applications: Utilize modern front-end frameworks and back-end technologies to build scalable, secure, and high-performance applications.
• Implement AWS Enterprise Solutions: Architect and deploy applications using AWS services such as AWS Lambda, Amazon EC2, Amazon S3, and Amazon RDS, ensuring best practices in scalability, security, and cost-efficiency.
• Collaborate Across Teams: Work closely with cross-functional teams to translate product goals into robust technical solutions, maintaining high technical standards.
• Ensure Code Quality and Best Practices: Conduct code reviews, implement testing protocols, and maintain comprehensive documentation to uphold code quality and maintainability.
• Stay Updated with Emerging Technologies: Keep abreast of the latest developments in AWS services, DevOps practices, and full-stack development trends to enhance our technology stack continually.

Qualifications

• Extensive Experience in Full-Stack Development: Proficiency with modern front-end frameworks (e.g., React, Vue.js) and back-end languages (e.g., Node.js, Python).
• Deep Expertise in AWS Services: Hands-on experience with AWS services including AWS Lambda for serverless computing, Amazon EC2 for scalable computing capacity, Amazon S3 for object storage, and Amazon RDS for managed relational databases.
• Knowledge of Cloud Architecture and Security: Understanding of AWS security protocols, compliance standards, and best practices for designing secure and resilient cloud architectures.
• Familiarity with DevOps Tools and Practices: Experience with containerization tools like Docker and orchestration tools like Kubernetes, as well as CI/CD pipelines for automated deployment and monitoring.
• Strong Problem-Solving Skills: Ability to troubleshoot complex issues and optimize application performance within AWS environments.
• Excellent Communication and Collaboration Skills: Proven ability to work effectively in distributed teams, communicate technical concepts clearly, and collaborate with stakeholders across various departments.
• Experience with AI/ML Integration: Familiarity with integrating AI and ML models into applications is a plus.