Freelancer - Full Stack Lead Engineer

We are seeking a Full Stack Engineer with 4+ years of experience in designing, developing, and deploying scalable applications. The role requires expertise across frontend, backend, mobile backend requirement gathering, AIdriven CI/CD pipelines, and prompt engineering with modern AI tools.

Key Responsibilities

• Application Development
• Build and maintain scalable web and mobile applications.
• Write clean, maintainable, and testable code.
• Mobile Backend Requirement Gathering
• Collect and analyze requirements for mobile backend services (authentication, push notifications, offline sync).
• Architect APIs optimized for mobile performance and reliability.
• Frontend Engineering
• Develop responsive UIs using React/Angular/Vue.
• Ensure accessibility and crossplatform compatibility.
• Backend Engineering
• Build RESTful/GraphQL APIs and microservices using Node.js/Java/Spring.
• Optimize database queries and schema design (SQL/NoSQL).
• Cloud & AIDriven CI/CD
• Deploy applications on AWS/Azure/GCP.
• Implement CI/CD pipelines with AIbased monitoring (predictive failure detection, automated rollback).
• Use containerization (Docker/Kubernetes) with intelligent scaling.
• Prompt Engineering with AI Tools
• Design and optimize prompts for AIpowered applications (e.g., chatbots, copilots, recommendation engines).
• Integrate AI APIs (OpenAI, Azure AI, Hugging Face) into backend workflows.
• Collaborate with product teams to leverage AI for automation, personalization, and analytics.
• Collaboration & Mentorship
• Work closely with product managers, designers, and QA teams.
• Mentor junior engineers and conduct code reviews.

Required Skills

• Frontend: React, Angular, or Vue; HTML5, CSS3, JavaScript/TypeScript.
• Backend: Node.js, Java/Spring Boot, Python/Django.
• Mobile Backend: Firebase, AWS Amplify, or custom APIs for mobile apps.
• Databases: MySQL, PostgreSQL, MongoDB.
• Cloud/DevOps: AWS, Azure, GCP, Docker, Kubernetes, Jenkins.
• AI in DevOps: GitHub Copilot, Harness, AIbased monitoring for CI/CD.
• Prompt Engineering: Crafting effective prompts, finetuning AI models, integrating LLM APIs.