A
Hands-On AI and Data Engineering Manager
PresencialTiempo completoAI EngineeringFinTechEnterprise Software
Lead a multidisciplinary engineering team delivering scalable AI-powered consumer experiences and data-driven product capabilities for a financial technology platform.
Responsabilidades
- Lead data scientists, data engineers, and product analysts.
- Own AI product delivery from research and experimentation through production operation.
- Provide hands-on technical direction for complex AI systems and maintain engineering quality standards.
- Integrate LLMs, AI agents, and intelligent workflows into consumer products.
- Design scalable architectures for AI-enabled applications and select technologies for AI platforms and data pipelines.
- Lead product data analysis and experimentation using metrics, dashboards, and user interaction insights.
- Establish prompt engineering frameworks, monitoring, evaluation, and feedback loops for AI outputs.
- Translate product goals into technical roadmaps and align AI capabilities with measurable outcomes.
Requisitos
- At least 6 years of software engineering experience building production systems.
- At least 2 years of engineering management or technical leadership experience.
- Strong experience building large-scale backend systems in Python.
- Experience developing modern web applications with React, Next, Angular, Vue, or comparable frameworks.
- Experience deploying, operating, evaluating, and iterating on LLM-based production systems.
- Strong understanding of data pipelines, experimentation, and product analytics.
- Experience with Google Cloud Platform, Amazon Web Services, or comparable cloud environments.
- Experience with prompt engineering, retrieval-augmented generation, vector databases, AI agents, or autonomous workflows.
Se valora
- Experience with ADK, A2A, LangChain, LangGraph, LlamaIndex, or equivalent frameworks.
- Experience with gRPC and protobuf-based architectures.
- Experience building MCP servers.
- Background in data engineering, experimentation platforms, or ML infrastructure.