Publicado hoy.
Backend Platform AI Engineer en HIRELINE
Sueldo oculto
Remoto: México
Empleado de tiempo completo
Inglés : Nivel Avanzado
Team and Responsibilities
We are seeking Senior AI/ML Engineers to join a new, forward-thinking AI team, established in Mexico City. This team will focus on building enterprise production-ready AI solutions at scale. The ideal candidates are technical operators with a strong backend platform focus who can drive innovation in the expense platform. Highly focused on cloud infrastructure and robust ML/system scaling.
Location: Mexico City: 1 o 2 times a month in-office presence
Advanced english required
What You'll Do:
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Design, develop, and deploy AI-driven services and workflows ("agents") for the American Express expense platform.
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Focus on RAG (Retrieval-Augmented Generation) implementations, fine-tuning models, and building robust LLM workflows in production.
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Develop solutions for key features such as recommendations, predictions, chatbots for dashboard analytics, and smart receipt generation.
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Implement high standards for observability, testability, and metrics for all AI models and systems.
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Work in a collaborative, fast-paced environment to deliver enterprise-grade solutions.
Required Technical Skills & Experience:
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Senior-level experience in developing production-ready, scalable enterprise solutions.
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Strong proficiency in Golang (at least 5 years) in backend engineer and React. Prior non-AI-related Golang experience is acceptable.
Strong applied experience with LLMs, RAG, fine-tuning, embeddings, and inference workloads.
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Hands-on experience building production AI systems (not only experimentation or prototypes).
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Strong knowledge of LLM mechanics, neural networks, prompting, embeddings, and evaluation.
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AI/ML Expertise: Deep understanding of the mechanics of LLMs, neural networks, training, fine-tuning, and AB testing/versioning models.
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Experience with cloud infrastructure and practical ML experience (especially for the Backend Platform Engineer role).
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Soft Skills: Strong professional working proficiency in English is required.
Excellent English communication; prior experience working with US-based teams is a strong plus.
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Candidates must have experience in implementing observability, testability, and metrics, as there is scrutiny on decisions made by AI models,
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Strong ownership and autonomous execution.
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Ability to work in fast-paced, ambiguous environments.
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Team-first mindset with a focus on collaboration and communication.
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“Technical operator” mentality—able to design, build, and run production systems end-to-end.