Sr. Full-Stack Software Engineer

Hyper Lychee Labs; India; Remote; INR 1,102,000 - 2,480,000; Part time

Benefits offered by this job

Flexible schedule

Remote work

Immediate start

Job summary

Hyper Lychee Labs is seeking highly skilled Full-Stack Software Engineers for an AI training project. You will contribute to front-end and back-end development, tackle complex tasks, and help translate and validate coding builds across languages.

You will work across the full stack, reviewing code, debugging, and ensuring quality. The role offers contractor hours (~15 per week) with flexible scheduling and potential weekend work.

Qualifications

• Hands-on experience with both frontend and backend engineering.
• Production experience with multiple programming languages.
• Ability to understand and contribute to complete software system architecture.
• Comfort working in unfamiliar codebases.
• Strong debugging and problem-solving skills.

Responsibilities

• Develop, modify, and debug front-end and back-end application components.
• Implement user-facing features and the services, APIs, and data models that support them.
• Work inside unfamiliar repositories and understand existing application architecture.
• Diagnose failures involving application state, API contracts, authentication, persistence, networking, and deployment.
• Evaluate and improve code written in multiple programming languages.
• Review AI-generated solutions for correctness, completeness, performance, security, and maintainability.

Skills

Full-stack engineering

Frontend development

Backend development

Debugging

System architecture

Tools

JavaScript/TypeScript

Python

Go

Job description

Job Type: Contractor (~15 hours per week)

Schedule: Flexible—you choose the hours and days you work, including weekends if desired as long as there is activity.

Job Description

We are looking for highly skilled Full-Stack Software Engineers to contribute to an AI training project involving software development, technical problem-solving, debugging, system architecture, and code evaluation.

The work involves creating, solving, reviewing, and validating challenging software-engineering tasks across front-end and back-end systems and helping with translating full coding builds from one particular language into another.

This role requires meaningful hands-on experience across both front-end and back-end engineering. Candidates should be comfortable working throughout the application stack rather than specializing exclusively in one layer.

What You'll Work On

• Develop, modify, and debug front-end and back-end application components.
• Implement user-facing features and the services, APIs, and data models that support them.
• Work inside unfamiliar repositories and understand existing application architecture.
• Diagnose failures involving application state, API contracts, authentication, persistence, networking, and deployment.
• Evaluate and improve code written in multiple programming languages.
• Review AI-generated solutions for correctness, completeness, performance, security, and maintainability.

Required Qualifications

• Meaningful hands-on experience with both front-end and back-end engineering.
• Production experience with multiple programming languages.
• Experience understanding and contributing to the architecture of complete software systems.
• Ability to work effectively in unfamiliar codebases.
• Strong debugging and technical problem-solving skills.

Process

• Complete an AI interview of approximately 30 minutes.
• Complete a technical assessment, if required.
• Complete the hiring manager review.

Compensation Structure

Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply. Experts must submit a minimum number of tasks per week.

Start Timeline and Availability

We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first tasks within 24–48 hours of completing onboarding.