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Job Description: AI & Data – AI EngineerLocation: Buenos Aires - Argentina (Hybrid)Clients: US-based Enterprise Clients About the Role The Senior AI Engineer designs, builds, and ships enterprise-grade AI/ML and LLM-based solutions.This role focuses on hands-on engineering, high-quality delivery, and strong collaboration with cross-functional teams.Key Responsibilities Design, build, and deploy AI/ML and LLM-based solutions in enterprise environments.Collaborate with cross-functional teams (Data Engineering, Cloud, Product) to deliver scalable AI systems.Ensure high engineering standards, maintainability, and best practices.Participate in code reviews, architecture discussions, and solution design.Support continuous improvement of AI delivery processes and tooling.Skills & Qualifications Python & DevelopmentAdvanced Python (3–6 years); FastAPI;scikit-learn; API design;clean code; Preferred: intermediate SQL, Design patterns (clean architecture/hexagonal); microservices; advanced testing; DockerWhat we evaluate: Code quality; API design; troubleshooting; software architecture discipline; applied SQL LLMs, RAG &Agents;: End-to-end RAG; LangChain/LangGraph;Vector search (FAISS or similar); Fine-tuning (LoRA/QLoRA); Advanced evaluation(RAGAS/TruLens/DeepEval); Agent designAutogen; Preferred:



Llama Index; custom retrieversWhat we evaluate: Hallucination mitigation; grounding; cost/latency trade-offs; quality Cloud (Azure orDatabricks):Cloud (Azure): Azure OpenAI; Azure AI Search; Azure ML; service integration; AKS/Container Apps; API ManagementDatabricks: Advanced MLflow (registry/tracking/serving); Delta Lake; Unity Catalog; Feature Store; Vector SearchPreferred: Workflows/DLT,What we evaluate: Secure & scalable architectures; integration; resilience, Pipelines; governance (Unity Catalog); productivityMLOps & Delivery: CI/CD (GitHub Actions/Azure DevOps); Docker;AKS/Kubernetes; End-to-end ML pipelines; Basic monitoring (latency, cost, failures)Preferred: AI observability (tracing/telemetry); advanced Bicep/TerraformWhat we evaluate: Reliability; diagnostics; automation ML Fundamentals: Classic models; Advanced metrics & trade-offs; When to use classicML vs. LLMsPreferred: Advanced/ensemble modelsWhat we evaluate: Technical judgment; model validation Communication and other requirements: English: Fluent B2+ technical communicationAutonomy in English, Technical clarity; ProactiveGood at managing request gathering and handlingProactive communication

Postúlate en Kit Empleo: kitempleo.com.ar/empleo/q1ubn

📌 Ai Engineer - Ey Gds (Buenos Aires)
🏢 WomenTech Network
📍 Buenos Aires