AI Engineer

About Us

Sharegain began with one question: If the largest institutions solely exercise the right to lend their stocks, bonds, and ETFs, what would it take to unlock this revenue opportunity for every investor?

Our team of experts in the UK, US and Israel built the solution: a platform that empowers online brokers, private banks, and wealth managers to offer securities lending to their clients. We call it SLaaS: Securities Lending as a Service. It’s a fully digital, customizable, end-to-end solution that automates front- and back-office operations. Institutions and investors are now free to earn more from what they own.

Every Sharegainer has their own backstory, but we all share an ambition to do things differently – bigger, better, and greater. Together we’re on a mission to democratize capital markets by building a more liquid world. The more we share, the more we all gain.

About The Role

We are looking for an experienced AI Engineer to join our R&D team. You will be delivering scalable web applications from idea to production, taking care of all aspects of software development – from technologies and security to scalability and reliability.

Responsibilities

• End-to-end ownership of AI & agent systems: take full ownership of your features from architecture and design through to implementation and production, including AI-native features such as autonomous agents and intelligent workflows. Own the full model quality lifecycle from experimentation through to production monitoring and improvement.
• Cloud infrastructure: be part of the design, maintenance, monitoring, and troubleshooting of our cloud applications.
• Technical excellence: drive technical excellence, high product quality, innovation, and timely delivery in a production-critical environment.
• Translate business needs into concrete system architecture and implement it end-to-end across the stack
  
  

• 6+ years of software development experience
• Proven LLM experience: write, optimize, and measure the effectiveness of AI prompts and applications. Rapidly experiment with models, prompts, and architectures using structured evaluation to identify the best solutions, and translate cutting-edge LLM capabilities into reliable, production-grade systems.
• Strong software engineering fundamentals: SOLID, TDD, version control systems (Git/GitHub/GitLab), and the ability to write production-ready code
• Deep understanding of Computer Science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance
• Familiarity with software architecture patterns such as microservices, CQRS, and event sourcing
• Experience with at least one major cloud provider (AWS, Azure, or GCP)
• Experience with Kubernetes and Docker containers
• Experience designing and building microservices architecture
• A team player with a positive attitude and a problem-solver mindset