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Undisclosed companyRamat Gan · Tel Aviv
Confirmed open at the employer 23 hours ago · Posted 10 days ago
Listing published by its original source and linked back to it. The employer did not pay JobsWarm for this listing.
As an AI & Quantitative Systems Engineer, you will work at the heart of LEAP’s proprietary real-time technology platform.
You will be a key connector between quantitative research, AI models, signal development, and production engineering. Your primary responsibility will be to transform research concepts, proprietary algorithms, quantitative models, and emerging AI capabilities into robust, scalable, production-grade systems.
You will work closely with LEAP’s lead developer, quantitative research team, and infrastructure team on systems that process real-time data, implement proprietary decision logic, and interact with external execution platforms.
This is a hands-on engineering role for someone comfortable moving between algorithms, AI, backend development, data processing, system architecture, and real-time production systems.
Key Responsibilities:
● Implement proprietary quantitative signals, algorithms, and decision logic in production.
● Translate quantitative research and experimental code into reliable real-time systems.
● Integrate models, algorithms, and data-driven components into production workflows.
● Design, build, and maintain production backend services, primarily in Python.
● Develop real-time, asynchronous, and event-driven system components.
● Integrate with broker platforms, external APIs, market-data services, and execution systems.
● Build internal tools supporting research, simulation, testing, monitoring, and production operations.
● Work across the technology stack when needed, including backend, data, APIs, and user-facing tools.
● Improve system performance, reliability, latency, scalability, and operational resilience.
● Diagnose complex production issues across application, data, execution, and infrastructure layers.
● Collaborate closely with quantitative researchers, infrastructure engineers, and DevOps.
● Contribute to architectural decisions and engineering standards across LEAP’s core platform.
Requirements:
● Strong track record of hands-on software engineering in production environments.
● Strong practical expertise in Python, particularly for backend and data-intensive applications.
● Strong practical expertise in backend development and data processing.
● Strong understanding of software architecture and system-engineering principles.
● Experience with real-time, asynchronous, and event-driven systems.
● Experience working with APIs, data pipelines, and distributed services.
● Ability to understand and implement mathematically and statistically driven logic.
● Strong analytical, debugging, and problem-solving capabilities.
● Ability and willingness to work across different languages and layers of the technology stack.
Advantages
● Experience with quantitative systems, algorithmic trading, financial technology, or market data.
● Experience with low-latency or high-throughput systems.
● Experience with broker APIs or execution platforms.
● Practical experience implementing or integrating AI and machine-learning technologies into production systems.
● Experience with LLMs, AI agents, agentic workflows, or AI orchestration frameworks.
● Full-stack experience, including React, JavaScript/TypeScript, and HTML/CSS.
● Experience with Redis, Kafka, PostgreSQL, or time-series databases.
● Experience with AWS and cloud-native environments.
● Strong background in mathematics, statistics, probability, optimization, or physics.
● Degree in Computer Science, Mathematics, Physics, Engineering, or a related field.
● Experience from elite technological environments such as 8200, MAMRAM, or equivalent programs.
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