AI Fullstack Engineer (Venado Tuerto)

Ryz Labs Ver todas las vacantes

  • Venado Tuerto, Santa Fe
  • Permanente
  • Tiempo completo
  • Hace 13 horas
RYZ Labs is looking for a highly skilled AI Fullstack Engineer to collaborate on cutting‑edge AI solutions that transform the integral supply chain. You’ll work with a forward‑thinking client to develop AI‑powered vision systems that analyze real‑world logistics operations. This is a unique opportunity to apply your expertise in AI and machine learning to solve high‑impact challenges in a rapidly evolving industry.
Basic Qualifications3–6 years of professional software engineering experience shipping production software.
Strong proficiency in TypeScript/Node.js and/or Python – comfortable on both backend and frontend.
Experience with React and modern frontend frameworks (Next.js preferred).
Solid understanding of relational databases (PostgreSQL) and API design (REST or GraphQL).
Practical experience building with LLM APIs – you’ve shipped something with them, not just experimented.
Working knowledge of Git workflows, Docker, and containerized environments.
Strong communication skills in English – you write clearly and engage well async.Key ResponsibilitiesShip complete, production‑ready features end‑to‑end: backend APIs, frontend UI, database schema, and tests.
Build and improve internal AI‑powered developer tools – things like automated bug triage, code generation assistants, and agentic workflows that help the team move faster.
Integrate LLM APIs and agentic patterns (tool use, multi‑step reasoning, prompt pipelines) into product features and internal systems.
Own and improve CI/CD pipelines, deployment workflows, and developer infrastructure to keep the team shipping safely and quickly.
Participate in code reviews, architecture discussions, and contribute to engineering standards on a small, collaborative team.
Debug and resolve production issues across the stack, including working with GCP services and containerized workloads.Nice to haveExperience with agentic architectures: tool use, agent loops, multi‑step LLM pipe

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