עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!

במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.

מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.

חברה בתחום כלכלה / ביטוח / פיננסים

תל אביב - יפו

חברה בתחום כלכלה / ביטוח / פיננסים

תל אביב - יפו
מלאה
18,000-25,000 ₪ הערכה מבוססת AI ולא שכר שהתקבל מהמעסיק
הערכה מבוססת AI ולא שכר של המעסיק

We're looking for a AI Backend Engineer with a data science foundation to join our AI team and build production systems that integrate Generative AI capabilities. You'll design and implement end-to-end solutions APIs, databases, orchestration, and cloud infrastructure for clients across a wide range of sectors.
This role is ideal for someone who thinks in systems, enjoys working with GenAI technologies, and wants to grow into designing complex architectures. You'll work alongside senior engineers on real delivery projects from day one.
Key Responsibilities:
Design and build backend systems APIs, databases, authentication, and integrations
Implement multi-agent architectures and orchestration workflows combining LLMs with backend logic
Deploy and maintain systems on GCP, Azure, or AWS
Optimize AI system performance, cost, and reliability
Collaborate with client teams, DevOps, and stakeholders on project delivery
Contribute to technical discussions and solution design.

Requirements:
Must Have:
1+ years of software development experience
Strong proficiency in Python for backend development
Experience building backend systems (APIs, databases, or services)
Solid understanding of data science fundamentals statistics, ML concepts, and working with data pipelines
Familiarity with at least one major cloud platform (GCP, Azure, or AWS)
Understanding of software engineering principles and architecture basics
Familiarity with GenAI / LLM concepts
Bachelor's degree in Computer Science, Data Science, or related field or equivalent practical experience
Advantages:
Experience with LLM provider APIs (OpenAI, Anthropic, Google)
Exposure to multi-agent systems or LLM-based workflows
Hands-on experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow)
Academic research or projects in AI, NLP, or data science
Personal or university projects involving multi-agent systems or ML model development
Docker and Kubernetes experience
Experience working on production systems in a client-facing environment.

This position is open to all candidates.