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

Celaralabs; Buenos Aires; Presencial; ARS 1.000.000 - 1.800.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Mentorship program

Opportunity to ship production code

AI tooling culture

Descripción de la vacante

Celaralabs is hiring a motivated Junior Fullstack Engineer with a strong backend focus to join a team building AI-powered products. You will write DRF endpoints, work with a React frontend, and contribute to data models and AI pipelines.

You will gain experience with Django, PostgreSQL, Redis, Docker, and modern frontend tooling, while shipping production code from day one and growing alongside senior engineers.

Formación

• Solid Python fundamentals; write clean, tested code.
• Familiarity with web APIs and HTTP request/response cycles.
• Experience with relational databases and basic schema design.
• Ability to debug AI-generated code and integration point failures.
• Interest in AI/ML tooling and RAG pipelines.

Responsabilidades

• Build API endpoints with DRF serializers and viewsets for React frontend.
• Extend AI agent capabilities and context retrieval systems.
• Write async tasks and workers for document parsing and LLM inference pipelines.
• Improve test coverage with pytest and database fixtures; catch N+1 queries.
• Ship frontend features with React/TypeScript, TanStack Query, and SCSS Modules.
• Debug AI output to reduce hallucinations and retrieval failures.

Conocimientos

Python fundamentals

Web APIs

Git

SQL queries

AI/LLM usage

Debugging AI output

Curiosity about AI/ML

Herramientas

Django

Flask

Docker

LangChain

LangGraph

TanStack Query

PostgreSQL

Redis

Descripción del empleo

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. 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.

Responsibilities

• 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.

Required

• 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

• 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.

Tech Stack

• 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.

Benefits

• 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.