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.
מלאה
30,000-45,000 ₪
We're hiring a senior AI Engineer to join our AI team building our autonomous AI agent and helping extend AI capabilities across the company.
What You'll Do
Design and ship our agent systems end-to-end - perception, reasoning, memory, retrieval, and the loops that connect them. Production agents, not prototypes.
Optimize multimodal inference for real-time operation at the edge - model choice, quantization, and batching to hit our latency and concurrency budgets.
Design embedding pipelines, vector storage, and hybrid retrieval that power the agent's search, behavioral analytics, and rule generation.
Architect how multiple edge units coordinate at scale - sharing context, correlating activity, and behaving as one coherent system for our largest deployments.
Build the agent's air-gapped lifecycle - updating, learning, and evolving entirely inside customer private networks with no cloud connectivity.
Run focused research on new open-source models and inference frameworks, and bring back insights and prototypes that inform our roadmap.
Plus occasional cross-company AI projects across the rest of the company.
What You'll Do
Design and ship our agent systems end-to-end - perception, reasoning, memory, retrieval, and the loops that connect them. Production agents, not prototypes.
Optimize multimodal inference for real-time operation at the edge - model choice, quantization, and batching to hit our latency and concurrency budgets.
Design embedding pipelines, vector storage, and hybrid retrieval that power the agent's search, behavioral analytics, and rule generation.
Architect how multiple edge units coordinate at scale - sharing context, correlating activity, and behaving as one coherent system for our largest deployments.
Build the agent's air-gapped lifecycle - updating, learning, and evolving entirely inside customer private networks with no cloud connectivity.
Run focused research on new open-source models and inference frameworks, and bring back insights and prototypes that inform our roadmap.
Plus occasional cross-company AI projects across the rest of the company.
Requirements:
We care about a particular mindset more than any specific item on a checklist. The person who'll thrive here is someone already living inside the modern AI stack - not planning to start. You read model release notes the way other people read the news. You've built real things with new tools the week they came out. Agentic dev workflows aren't something you've heard about; they're how you already work. When a new model drops, your first instinct is to put it on the bench. And underneath all of it, you're a builder - you ship, you write clean software, and you think about latency, cost, and what the user actually needs.
What We're Looking For
6+ years of software engineering experience, with the last few focused on AI / ML systems
Deep, hands-on experience designing and shipping agent systems in production - not demos. You understand agent architectures, memory, tool use, evaluation, and the failure modes that matter at scale.
Strong fundamentals in embeddings, RAG, and hybrid retrieval, with real experience designing vector storage and retrieval pipelines for production use
Deep production backend foundations - strong Postgres knowledge (functions, triggers, indexes, extensions, atomic operations, and similar depth), real-time client channels (WebSockets, SSE), async and event-driven backbones (pub/sub, queues, background tasks, webhooks), the ability to design systems and features around multithreading and multiprocessing, and dynamic resource management for high-throughput, latency-sensitive workloads.
Excellent architecture instincts and strong Python - you write code that scales and that other engineers can build on
Product sensibility - you can reason about trade-offs and what's worth building, not just what's technically possible
We care about a particular mindset more than any specific item on a checklist. The person who'll thrive here is someone already living inside the modern AI stack - not planning to start. You read model release notes the way other people read the news. You've built real things with new tools the week they came out. Agentic dev workflows aren't something you've heard about; they're how you already work. When a new model drops, your first instinct is to put it on the bench. And underneath all of it, you're a builder - you ship, you write clean software, and you think about latency, cost, and what the user actually needs.
What We're Looking For
6+ years of software engineering experience, with the last few focused on AI / ML systems
Deep, hands-on experience designing and shipping agent systems in production - not demos. You understand agent architectures, memory, tool use, evaluation, and the failure modes that matter at scale.
Strong fundamentals in embeddings, RAG, and hybrid retrieval, with real experience designing vector storage and retrieval pipelines for production use
Deep production backend foundations - strong Postgres knowledge (functions, triggers, indexes, extensions, atomic operations, and similar depth), real-time client channels (WebSockets, SSE), async and event-driven backbones (pub/sub, queues, background tasks, webhooks), the ability to design systems and features around multithreading and multiprocessing, and dynamic resource management for high-throughput, latency-sensitive workloads.
Excellent architecture instincts and strong Python - you write code that scales and that other engineers can build on
Product sensibility - you can reason about trade-offs and what's worth building, not just what's technically possible
This position is open to all candidates.
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.
תל אביב - יפו
ערב
7 חודשים
