Sr. Full-Stack Software Engineer - Remote

Location: Integral, Fully Remote
Job Type: Contractor | ~15 hours/week
Schedule: Flexible

We're looking for experienced Full-Stack Software Engineers to support an AI training project focused on software development, debugging, code evaluation, and technical problem-solving.

Key Responsibilities

- Develop and debug front-end and back-end applications.
- Build features, APIs, services, and data models.
- Understand and work across unfamiliar codebases.
- Troubleshoot application, API, database, and integration issues.
- Review and evaluate AI-generated code for correctness, security, performance, and maintainability.
- Translate and adapt software builds between programming languages.

Required Skills

- Python
- React
- JavaScript
- Java
- Node.js
- Rust
- Go
- TypeScript
- Strong full-stack development experience
- Experience with APIs, databases, application architecture, and debugging

Senior/Staff Software Engineer (AI-Native/Claude Code/Codex) · LATAM

- Location: Anywhere in LATAM
- Job Type: 100% Remote
- Engagement: Full-time Contractor
- Payment: USD
- Project: AI-Native LegalTech / M&A; SaaS Platform
- Seniority: Senior / Staff
- English Level: B2 / C1

Get to Know Darwoft

At Darwoft, we build digital products with heart. We're a Latin American technology company focused on creating impactful, human-centered software in partnership with companies around the globe.

Our remote-first culture is built on trust, continuous learning, collaboration, and strong engineering standards.



We work with international teams solving complex product and technology challenges where our engineers can have a direct impact on the product.

If you're looking for a place where your technical judgment matters and where you can contribute beyond simply executing tickets, welcome to Darwoft.

About the Opportunity

We're partnering with an innovative software company building a modern transaction platform for organizations managing complex M&A; processes.

The platform brings together document workflows, collaboration, approvals, diligence, transaction management, and AI-powered capabilities within a single SaaS product.

What makes this opportunity particularly different is the way the engineering team builds software.

The product has been developed using an AI-native engineering approach , with tools such as Claude Code, OpenAI Codex, and other AI coding agents deeply integrated into the development workflow.

We're looking for a highly experienced Senior / Staff Software Engineer who can combine strong software engineering fundamentals with this new way of building software.

This is not a traditional AI/ML Engineer role .

You won't be training machine learning models or working primarily on Data Science. Instead, you'll be engineering production software,



navigating a large existing codebase, making architectural decisions, improving reliability, and using AI coding agents to dramatically increase development velocity.

The ideal person is a builder first : highly technical, pragmatic, product-oriented, low-ego, and comfortable taking ownership of complex systems.

What You'll Be Doing

- Navigate, understand, and evolve a large existing production codebase.
- Design and implement new product capabilities across a complex SaaS platform.
- Make pragmatic architectural and system design decisions as the product continues to scale.
- Identify technical debt, architectural risks, reliability issues, and opportunities for improvement.
- Use Claude Code, Codex, Cursor, Copilot, or similar AI coding agents extensively throughout the software development lifecycle.
- Leverage AI agents to explore codebases, design implementations, generate and refactor code, debug issues, write tests, and accelerate delivery.
- Build and evolve backend services, APIs, integrations, data models, and application workflows.
- Contribute across the application stack when needed.
- Strengthen automated testing, maintainability, observability, reliability, and production readiness.
- Improve development workflows, tooling, automation, and engineering practices.
- Troubleshoot complex issues across application, data, and infrastructure layers.
- Balance development speed with software quality and long‑term maintainability.
- Work closely with product leadership to translate business problems into eff

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