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Hands-On AI and Data Engineering Manager

april·Израиль·en
В офисеПолная занятостьAI EngineeringFinTechEnterprise Software

Lead a multidisciplinary engineering team delivering scalable AI-powered consumer experiences and data-driven product capabilities for a financial technology platform.

Обязанности

  • 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.

Требования

  • 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.

Будет плюсом

  • 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.

Соответствие

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