Senior AI Engineer - Agentic Systems
פורסם 21 ביוני · 41 מועמדים
התפקיד במילים פשוטות
התפקיד כולל פיתוח והובלה של מערכות בינה מלאכותית וסוכנים חכמים (AI agents) הפועלים בסביבת ייצור, לצד ארכיטקטורה והרחבה של מערכות בקאנד מבוזרות מבוססות Python. העבודה משלבת שילוב של מודלי שפה גדולים (LLMs), תהליכי חשיבה ואינטגרציה עם תשתיות תוכנה אמינות. בנוסף, התפקיד דורש קבלת החלטות טכניות מרכזיות ושיתוף פעולה הדוק עם צוותי מוצר, אבטחה ומחקר.
- 5+ years of software engineering experience
- Strong software engineering background, with the ability to build production-grade systems beyond research, experimentation, or prompt engineering
- Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems
- Strong backend expertise, including Python, distributed systems, and cloud-native architecture
- Experience designing systems that balance AI components with reliable backend infrastructure
- Experience working in a fast-paced startup environment
חולץ מתיאור המשרה · מתעדכן אוטומטית
למי זה מתאים
התפקיד מתאים למהנדסי תוכנה מנוסים עם לפחות 5 שנות ניסיון, בעלי רקע חזק בפיתוח מערכות בקאנד מבוזרות וניסיון מעשי בבניית מערכות AI/LLM פרודקשן. הוא פחות יתאים למי שאין לו ניסיון מעשי מוכח מעבר לשלב המחקר או הנדסת הפרומפטים.
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןConifers.ai is transforming security operations centers (SOCs) with CognitiveSOC™, its AI SOC platform, enabling enterprises and MSSPs to achieve SOC excellence.
By leveraging agentic AI, Conifers helps security teams investigate complex, multi-tier incidents with speed, accuracy, and trust.
Led by seasoned cybersecurity leaders and backed by SYN Ventures, PICUS Capital, and others, the company brings deep industry knowledge and innovation to an increasingly AI-driven threat landscape.
You’ll build real AI systems running in production, where intelligent agents and robust backend architecture work together to investigate security incidents for real customers.
If you enjoy turning cutting-edge AI into reliable, scalable production systems, you’ll feel at home here.
What You’ll Do :
Design, build, and ship major end-to-end features
Lead development of AI agents operating in production environments
Architect and scale Python-based distributed backend systems
Make key technical decisions that shape the evolution of an AI-first platform
Build systems that combine LLMs, reasoning flows, orchestration, and classic backend engineering
Work closely with Product, Design, Security Researchers, and GTM teams
Bring clarity, ownership, and strong engineering standards to the team
What You’ll Bring :
5+ years of software engineering experience
Strong software engineering background, with the ability to build production-grade systems beyond research, experimentation, or prompt engineering
Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems
Strong backend expertise, including Python, distributed systems, and cloud-native architecture
Experience designing systems that balance AI components with reliable backend infrastructure
Ability to take ambiguous problems and turn them into structured, scalable solutions
Strong ownership mindset and bias for action
Full professional fluency in English
Nice to Have :
Experience in the cybersecurity domain
Experience building security or AI-driven products
Experience working in a fast-paced startup environment
Our Commitment
We are an equal opportunity employer and value diversity at our company. All qualified applicants will receive consideration without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
#LI-AM1 #LI-Hybrid
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שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- היברידי
- 5+ years of software engineering experience, Strong software engineering background, with the ability to build production-grade systems beyond research, experimentation, or prompt engineering, Hands-on experience building and operating production-grade AI/LLM systems, ideally including agentic workflows, tool-calling, orchestration, evaluations, or multi-step reasoning systems, Strong backend expertise, including Python, distributed systems, and cloud-native architecture, Experience designing systems that balance AI components with reliable backend infrastructure