AI Engineer (Fintech)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
AI Engineer (LLM/Fintech): Building and delivering scalable AI and agent systems for a securities lending platform with an accent on autonomous agents, intelligent workflows, and model quality lifecycles. Focus on translating cutting-edge LLM capabilities into production-grade systems and designing scalable cloud architecture.
Location: Hybrid (Netanya, Israel)
Company
provides a fully digital, end-to-end SLaaS (Securities Lending as a Service) platform that empowers brokers and wealth managers to offer securities lending to their clients.
What you will do
- Take end-to-end ownership of AI and agent systems, including the design and implementation of autonomous agents and intelligent workflows.
- Manage the full model quality lifecycle, from initial experimentation to production monitoring and iterative improvement.
- Design, maintain, and troubleshoot cloud infrastructure for scalable web applications.
- Translate complex business needs into concrete system architecture and implement them across the entire stack.
- Drive technical excellence, innovation, and high product quality in a production-critical environment.
Requirements
- 6+ years of professional software development experience.
- Proven experience with LLMs, including writing, optimizing, and measuring the effectiveness of AI prompts and applications.
- Strong software engineering fundamentals, specifically SOLID, TDD, and proficiency with Git.
- Deep understanding of Computer Science fundamentals, including data structures, algorithms, and performance complexity.
- Experience with software architecture patterns such as microservices, CQRS, and event sourcing.
- Hands-on experience with Kubernetes, Docker, and at least one major cloud provider (AWS, Azure, or GCP).
Culture & Benefits
- Opportunity to work in a global team spanning the UK, US, and Israel.
- Mission-driven environment focused on democratizing capital markets.
- High level of ownership and impact on the product's AI capabilities.
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