Full Stack Engineer

• Design, develop, test, and deploy robust, scalable, and secure web applications.
  
• Work on both front-end (UI/UX, web frameworks) and back-end (APIs, business logic, databases).
  
• Collaborate with cross-functional teams, including product managers, designers, QA, and DevOps, to deliver high-quality solutions.
  
• Participate in architectural discussions and contribute to technology decisions.
  
• Write clean, maintainable, and reusable code with proper documentation.
  
• Optimize applications for performance, scalability, and reliability.
  
• Implement security and data protection best practices.
  
• Perform code reviews, mentor junior developers, and ensure coding standards are followed.
  
• Troubleshoot, debug, and resolve production issues.
  
• Stay up to date on emerging technologies and propose improvements.

Requirements

• Core Engineering: 4+ years of professional backend development experience with Python.
  Front End: Strong proficiency in front-end technologies: HTML5, CSS3, PHP, JavaScript, React.
• Back End: Solid experience with back-end technologies: Java/Spring Boot/Node.js.
  
• Web Frameworks: Expert proficiency with Fast API (preferred) or Flask/Django for building microservices.
  
• Cloud Native: Hands-on experience with AWS core services: Compute: Lambda, EC2, Fargate/ECS, and Networking: API Gateway, Load Balancers, VPC configuration.
  
• Containerization: proficiency in Docker (Multistage builds, optimization) and basic Kubernetes concepts
  
• Experience with CI/CD pipelines and build tools.
  
• Databases: Strong SQL skills and experience working with relational databases (MySQL/RDS) and NoSQL databases (DynamoDB).
  
• Version Control: Knowledge of version control systems (Git/Bitbucket).
  
• Strong problem-solving skills, analytical thinking, and attention to detail.
  
• Excellent communication and collaboration skills.

Preferred Skills (Nice to Have)

• Infrastructure as Code (IaC): Experience using Terraform or AWS CDK to provision cloud resources programmatically.
  
• ML Ops Familiarity: Experience working alongside Data Scientists, understanding the unique challenges of serving large models (GPU management, cold starts).

Basic Qualifications

• BS in Computer Science, Engineering, or a related field.
  
• Experience in product development, preferably in SaaS and cloud environments.
  
• Proven track record of taking software projects from concept to production deployment.
  
• Experience or understanding of the Intellectual Property (IP) domain is highly desirable.