Senior AI-Native Software Engineer (Frontend & Backend) Remote

Motorolasolutions

La Pampa

Remote

ARS 230,602,000 - 322,843,000

Full time

3 days ago

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Benefits offered by this job

Contractor-style USD payment

100% remote work

Argentina holidays

English classes

Referral program

Learning platforms

Job summary

Darwoft is seeking a Senior/Staff Software Engineer for LATAM, remote, to join an AI-native, transaction-platform project.

You will navigate a large production codebase, architect scalable solutions, and drive delivery using AI coding agents. A strong background in backend/full-stack, APIs, data modeling, and cloud practices is essential. You will collaborate with leadership to balance speed with quality.

Qualifications

Production software built and operated at scale.
Strong fundamentals in architecture, system design, debugging, testing and maintainability.
Experience with large or complex existing codebases.
Backend or full-stack engineering with modern languages and frameworks.
Experience building modern web apps and SaaS products.
Knowledge of APIs, architecture, integrations, data modeling and distributed systems.
Experience with relational databases and production data environments.
Automated testing and modern software development practices.
Familiarity with cloud environments, CI/CD, deployments, and production operations.
Ability to reason about trade-offs and make pragmatic decisions.
Strong ownership and ability to work independently.
Product mindset: understand not only how but why to build.

Responsibilities

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 scales.
Identify technical debt, risks, reliability issues, and opportunities for improvement.
Use Claude Code, Codex, Cursor, Copilot, or similar AI agents throughout the SDLC.
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 workflows.
Contribute across the application stack when needed.
Strengthen automated testing, observability, reliability, and production readiness.
Improve development workflows, tooling, automation, and engineering practices.
Troubleshoot complex issues across layers.
Balance speed with quality and long-term maintainability.
Work with product leadership to translate business problems into technical solutions.
Help a small team achieve greater development leverage through AI-assisted engineering.