SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Tabby is a fintech platform that has reshaped how people shop, earn, and save, serving over 15 million users globally. The company enables shoppers to split payments online and in-store with no interest or fees, partnering with 40,000+ brands including Amazon, Noon, IKEA, and SHEIN. Tabby processes over $10 billion in annual transaction volume and is the largest, fastest-growing fintech in the GCC region, valued at $4.5 billion with $1 billion+ in funding.
You will join a very early-stage initiative to build an internal AI agent platform—a transformative project that will scale into a powerful ecosystem impacting multiple business areas. This is a ground-floor opportunity to shape architecture and strategy from inception. You'll work at the intersection of large-scale distributed systems and AI technologies, designing and implementing backend services that integrate LLMs and agent frameworks deeply into core internal tools and automation.
Key responsibilities include developing the backend for the AI agent platform and supporting microservices, participating in architecture decisions and technology selection, staying current with AI agent frameworks and innovations, optimizing platform components for agent creation and quality evaluation under load, and collaborating closely with platform clients to incorporate feedback and ensure a user-friendly product.
You'll work with a world-class remote engineering team spread across 20+ countries, using modern tech including Golang, Python, PostgreSQL, Redis, Kubernetes, Google Cloud Platform, and a microservices architecture. The role requires 5+ years of backend engineering experience with at least 2 years each in Golang and Python. Experience with AI agent frameworks (Langchain, Langgraph, ADK), LLM-based features, agent-centric architectures, and ML model learning/evaluation in production is highly valued. You should have a track record building scalable distributed systems, experience with internal tools and automations, and a commitment to clean, testable, maintainable code.
