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.
You will design, build, and operate LLM-based and agentic systems as part of cross-functional teams, contributing to both greenfield initiatives and the evolution of existing GenAI platforms. You will develop strong foundations in system architecture, backend engineering, and cloud-based GenAI delivery while working closely with more experienced engineers.
Key Responsibilities:
GenAI Development & Implementation:
Develop end-to-end GenAI solutions from POC through production deployment
Implement backend microservices and GenAI components using Python
Contribute to the development of multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs within larger system
Participate in evaluating and improving system performance, scalability, reliability, and cost efficiency
Client Engagement & Collaboration:
Participate in technical discussions with clients and contribute to solution design discussions
Support presentations, demos, and technical explanations for client stakeholders
Collaborate closely with project managers, full-stack developers, and automation teams to deliver end-to-end solutions
Cloud & Platform Work:
Deploy and operate GenAI systems on GCP, Azure, and/or AWS
Work with cloud-native AI services and managed platform
Contribute to monitoring, reliability, and operational stability of production environments
Strong proficiency in Python for backend development and AI-related systems
Solid understanding of large language models and generative AI techniques
Experience contributing to agent-based workflows or orchestration logic
Practical experience with prompt design and prompt optimization techniques
Understanding of microservices architecture and API-based system design
Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience:
Up to 2 years of experience in software engineering, AI, or ML-related roles
Experience contributing to production or production-adjacent systems
Exposure to client-facing or consulting-style project delivery is an advantage
Education & Background:
Bachelors degree in Computer Science, AI, Machine Learning, or related technical field
(or equivalent practical experience and portfolio)
Soft Skills:
Strong analytical and problem-solving abilities
Clear technical communication skills
Ability to collaborate effectively across teams
Adaptability and eagerness to learn in fast-paced environments
Consulting mindset and client-oriented approach
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.
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