Mid-level AI Engineer

Job Description

Job Title: Mid-level AI Engineer

Job Type: Full-time

Location: Buenos Aires (Hybrid or Remote)

Experience: 2-4 Years of Relevant Experience

Job Summary:

Join our team as a Mid-level AI Engineer and help drive the next generation of GenAI-powered applications. You will architect robust solutions, collaborating closely with fellow engineers, product managers, and designers to turn cutting-edge research into real-world impact. If you thrive in a fast-paced, innovation-driven environment and are passionate about clear communication, this is the opportunity for you.

Responsibilities:

1. Build GenAI applications such as question-answering systems, content generation tools, and extraction pipelines.
2. Design, implement, and optimize RAG pipelines end-to-end: ingestion, chunking, embedding, prompt templating, evaluation, and deployment.
3. Develop robust APIs using Python frameworks (FastAPI preferred).
4. Work with multiple LLMs (OpenAI, Mistral, Anthropic, etc.) and evaluate model performance for different use cases.
5. Use LangChain, LangGraph, or LangSmith to orchestrate and monitor GenAI workflows.
6. Deploy applications on AWS or Azure and implement CI/CD for continuous improvement.
7. Collaborate with data engineers and product managers to translate technical designs into scalable solutions.
8. Participate in system design discussions, contributing ideas for performance and maintainability.

Must-have Skills:

1. Python: Strong experience with the language. Able to design clean, modular, production-grade code.
2. API Development: Proven experience building and maintaining APIs (FastAPI/Flask).
3. GenAI Stack: LangChain, LangGraph, LangSmith; multiple LLM APIs (OpenAI, Mistral, etc.).
4. RAG Lifecycle: Data ingestion, prompt templating (Jinja), evaluation/re-ranking, deployment.
5. Cloud/DevOps: Hands-on with AWS or Azure (deployments, monitoring).

Good-to-have Skills:

1. Understanding of distributed systems and scaling strategies.
2. Experience with containerization (Docker) and orchestration (Kubernetes).
3. Familiarity with Guardrails AI or Responsible AI frameworks.
4. Basic UI integration knowledge (React, optional).