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naukri

Senior Backend Engineer II

tabby
Dubai, UAE
Senior
1 months ago
GolangPythonPostgreSQLRedisKubernetesGoogle Cloud Platform
Free

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GolangPythonPostgreSQL
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About Tabby

  • Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money.
  • Over 15 million users choose Tabby to stay in control of their spending and make the most out of their money.
  • Tabby generates over $10 billion in annual transaction volume for its partner brands and is the highest rated, most reviewed, largest, and fastest growing FinTech in the GCC region.

Role Overview

  • We're looking for a Senior Backend Engineer to help us build an internal AI agent platform.
  • You'll be joining a very early stage initiative to build an internal platform for an AI agent ecosystem.
  • You'll work with cutting edge technologies, including LLMs and agent frameworks, designing architectures at the intersection of large scale services and AI.

Requirements

  • 5+ years of backend engineering experience, with at least 2 years working with Golang and 2 years working with Python
  • Plus will be an experience with AI agent frameworks: Langchain, Langgraph, ADK
  • Plus will be an experience in building or integrating LLM based features and agent centric architectures.
  • Big plus will be an ML experience: learning and evaluation of models, implementation of them in production
  • Experience building scalable, distributed systems and working with high load architectures
  • Solid understanding of backend tools and technologies we use: PostgreSQL, Redis, Kubernetes, Google Cloud Platform, GitLab, and a microservices architecture
  • Experience developing internal instruments, automations, CRM and so on
  • A passion for writing clean, testable, and maintainable code
  • A proactive mindset and the ability to work independently
  • Strong communication skills in English (B2 level or higher)

Responsibilities

  • Development of backend for AI agent platform and microservices around it
  • Participate in the architecture setup, in choosing technologies
  • Stay up to date with updates and frameworks around AI agent technologies, study and experiment.
  • Improve and optimize parts of the platform related to agent creation, quality evaluation, and performance under load.
  • Work closely with platform clients, take feedback into account, and help build a user friendly product.

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