AI/Backend Orientation

- Education: Systems Engineering degree or equivalent formal education/practical experience.

- Seniority: 5+ years of total software engineering experience, with 2+ years of hands-on experience building and deploying production-grade AI-powered applications.

- Core Stack: Python (FastAPI), Major Cloud Provider (GCP, AWS, or Azure), Machine Learning / GenAI APIs.

- Backend Must-Haves: Microservices architecture, system design, containerization (Docker/Kubernetes) *desirable, message-driven architectures (e.g., Pub/Sub, Kafka, SQS), and relational/non-relational databases.

- AI Must-Haves: LLM orchestration frameworks (e.g., LangChain, LlamaIndex, LangGraph), API integration, Prompt Engineering, production RAG architectures, and multi-agent systems.

- Nice-to-Haves: Experience with Google Cloud Platform (specifically Cloud Run, Vertex AI, GCS), basic MLOps (model serving, feature stores), and LLM evaluation/observability frameworks.

- Soft Skills: Ability to write PRDs and RFCs, break down vague business requirements into clear technical tasks, and take end-to-end feature ownership.

- Languages: English (C1/Fluent)

📌 Machine Learning Engineer (México)
🏢 E-Solutions
📍 México