Python Gen Ai Developer

Madiff Polska

Lisboa

Presencial

EUR 65 000 - 111 000

Tempo integral

Há 6 dias
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Vantagens oferecidas por esta oferta de emprego

Competitive daily rate
International GenAI projects
Multilingual environment
Private medical care

Resumo da oferta

Madiff Polska is seeking an experienced AI Engineer (Python Backend) to build backend systems for GenAI-powered applications used by leading US clients in banking, fintech, and payments. You will design microservices in Python and integrate with LLM APIs, implementing RAG pipelines with Pinecone/Chroma to boost contextual intelligence.

Collaborate with teams in the US and Europe, deploy in cloud (Azure/AWS), and ensure scalable, secure AI solutions using Docker and modern data stores like

Qualificações

  • 3–4+ years backend experience with Python (Django, Flask, FastAPI).
  • 1–2+ years working with GenAI, LLM APIs, or vector databases.

Responsabilidades

  • Design and develop backend microservices in Python powering GenAI applications.
  • Integrate with LLM APIs and implement RAG pipelines using vector databases.
  • Develop AI workflow orchestration using LangChain and LangGraph.
  • Build APIs and backend modules connecting to financial systems and customer platforms.
  • Manage data pipelines with PostgreSQL, MongoDB, and data lakes.
  • Deploy and maintain services using Docker and cloud environments (Azure/AWS).
  • Collaborate with cross-functional teams in US and Europe to deliver production-grade AI capabilities.

Conhecimentos

Python backend (Django/Flask/FastAPI)
GenAI/LLM APIs
LangChain/LangGraph
Docker & Cloud (Azure/AWS)
English (B2+)
Banking/Fintech domain

Ferramentas

PostgreSQL
MongoDB
Pinecone
Chroma

Descrição da oferta de emprego

Python GEN AI developer

Empresa : Madiff Polska
Tipo de Emprego : Periodo Integral
Lisbon, Portugal

Descrição do Emprego - Python GEN AI developer

Weâre looking for an experienced AI Engineer (Python Backend) to join our team building backend systems for GenAI-powered applications used by leading US clients in banking, fintech, and payments. The projects involve designing intelligent automation tools, data-driven decision engines, and secure AI integrations for enterprise-grade environments.

  • Design and develop backend microservices in Python (Django, Flask, or FastAPI) powering GenAI applications and internal automation platforms.
  • Integrate with LLM APIs (OpenAI, Anthropic) and implement RAG pipelines using vector databases such as Pinecone or Chroma to enhance contextual intelligence.
  • Develop AI workflow orchestration â prompt routing, retrieval logic, tool execution, memory handling, and multi-agent collaboration â using LangChain and LangGraph.
  • Build APIs and backend modules that connect to financial systems, credit decision engines, and customer experience platforms.
  • Manage structured and unstructured data pipelines, integrating with PostgreSQL, MongoDB, and data lakes.
  • Deploy and maintain services using Docker and cloud environments (Azure or AWS), ensuring scalability, performance, and security compliance.
  • Collaborate with cross-functional teams in the US and Europe, including frontend, DevOps, and data science units, to deliver production-grade AI capabilities.
Requirements
  • 3â4+ years of backend experience with Python (Django, Flask, or FastAPI).
  • 1â2+ years working with GenAI, LLM APIs, or vector database architectures.
  • Practical knowledge of LangChain, LangGraph, embeddings, and retrieval frameworks.
  • Strong experience with Docker, Git, CI/CD, and cloud services (Azure or AWS OR GCP).
  • Understanding of prompt optimisation, token management, and AI system integration.
  • Experience in enterprise or banking environments is a strong advantage.
  • B2+ English and ability to collaborate with global engineering teams.
Benefits
  • Competitive daily rate.
  • Opportunity to work on international GenAI projects for top-tier US clients.
  • Dynamic, multilingual work environment and access to advanced AI infrastructure.
  • Private medical care and long-term project engagement.
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