Fullstack Engineer JR (Backend + AI) (NW - FS - 20260609)

Argentina·Buenos AiresContractentry

EngineeringFullstack Developer

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Quick Summary

Overview

Role Overview We are looking for a motivated Junior Fullstack Engineer with a strong backend focus who is eager to build great products and grow alongside a team that embraces cutting-edge technology.

Technical Tools

EngineeringFullstack Developer

We are looking for a motivated Junior Fullstack Engineer with a strong backend focus who is eager to build great products and grow alongside a team that embraces cutting-edge technology. You write clean, thoughtful code, care about building reliable systems, and are genuinely curious about how AI development tools (like Cursor or Claude) can make you a faster, better developer from day one.

Build API endpoints — write DRF serializers and viewsets serving data to a React frontend, working with complex models (JSONFields, custom managers, mixin patterns).
Extend AI agent capabilities — add new tools to agents; work on context engineering, and retrieval systems.
Write async task workers — build and debug distributed RQ worker logic covering document parsing (PDF, Excel, PowerPoint) and LLM inference pipelines.
Improve test coverage — write pytest tests with real database fixtures, mock external APIs, and catch N+1 query issues.
Ship frontend features — build React/TypeScript components wired to TanStack Query, styled with SCSS Modules; work with rich text, interactive charts, and virtualized tables.
Debug AI output — diagnose and fix hallucinations and retrieval failures in agent pipelines.

Solid Python fundamentals — classes, tracebacks, data structures, without over-relying on AI autocomplete.
Familiarity with web APIs: HTTP methods, JSON serialization, request/response cycles.
Comfort with Git: branching, rebasing, resolving merge conflicts.
Experience with at least one relational database: SQL queries and basic schema design.
Comfortable working with AI-based tools like Cursor, Claude Code, etc.
Genuine curiosity about AI/ML — LLM API usage, a RAG pipeline, or serious experimentation beyond chatting with ChatGPT.
Ability to debug AI-generated code — shipping broken AI output is worse than writing it yourself.

Nice to Have

~1 min read

Django or Flask experience.
React/TypeScript exposure, even from a personal project.
Familiarity with Docker and containerized development.
Experience with vector databases, embeddings, or LLM orchestration (LangChain, LangGraph, etc.).
A deployed project you can demo — valued more than GPA.

Backend: Python 3.13, Django 5.2, Django REST Framework, PostgreSQL, Redis.
AI/ML: OpenAI, Anthropic & Google LLM APIs; LangChain + LangGraph; sentence-transformers; RAGAS.
Data: NumPy, Pandas, Polars, scikit-learn, XGBoost, PyMC, Prophet, Plotly.
Frontend: React 19, TypeScript, Vite, Ant Design, TanStack Query, SCSS Modules.
Infra: Docker, GitHub Actions CI/CD, AWS (S3, ECR), MinIO, Sentry, RQ.

Mentorship and hands-on learning alongside senior engineers.
Opportunity to ship production code from day one on a real AI platform.
A culture that embraces AI tooling, rigorous testing, and continuous tech innovation.