AI-Native Engineer, New Grad (Ingeniero/a de Software AI-Native — Inicio de Carrera) - Mexico City (Hybrid)
Salary not listed • Mexico City / CDMX / Mexico • Full-time
Posted 2mo ago
This job has been open for more than 60 days. It may no longer be actively hiring, so check with the company before putting a lot into an application.
About the job
Clara is seeking an AI-Native Engineer to join their team in Mexico City. This role is designed for individuals at the start of their software careers, offering the opportunity to ship production code and own features end-to-end within weeks. You will leverage AI across your entire workflow, from coding and debugging to research and automation, pushing the boundaries of how AI is used within the team. The role involves deep learning of the B2B fintech domain in Latin America, working directly with Product, Design, and senior engineers to build impactful solutions.
Responsibilities
- Ship production code and real features within the first few weeks.
- Own features from design and build through testing, deployment, and monitoring.
- Utilize AI across the development workflow, including coding, debugging, testing, and research.
- Push the frontier of AI usage within the engineering team.
- Collaborate directly with Product, Design, and senior engineers.
- Gain a deep understanding of the B2B fintech domain in Latin America.
Requirements
- At the start of a software career, with no prior full-time software experience required.
- A strong technical foundation in Computer Science, Software Engineering, Mathematics, Physics, or equivalent demonstrated ability.
- Proven experience building projects, demonstrable via GitHub, deployed apps, or open-source contributions.
- Demonstrated experience building with AI, including agents, RAG, evals, or fine-tunes, and daily use of AI coding tools.
- Strong fundamentals in data structures, algorithms, and systems thinking.
- Proficiency in English for technical communication.
Benefits
- Competitive salary
- Stock options (ESOP) from day one
- Annual learning budget
- Accelerated development paths