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GSSTech Group

GenAI Software Engineer - Node.js & LLMs

GSSTech Group · Dubai, Dubai, United Arab Emirates

IT Services and IT Consulting · 201-500 employees

9 h ago
Senior (5-10 yrs) Full-time United Arab Emirates
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About the role

Design and develop scalable backend applications using Node.js and TypeScript while integrating LLMs and enterprise data sources. Collaborate with cross-functional teams to build production-grade AI workflows and optimize performance for risk and compliance initiatives.

What they look for

Node.js TypeScript Generative AI LLMs Express.js PostgreSQL MongoDB Redis Vector Databases Azure AWS LangChain LangGraph Prompt Engineering RESTful APIs CI/CD

Requirements

Requires strong expertise in Node.js, modern AI frameworks like LangChain, and cloud-based AI services from Azure and AWS. Candidates must possess a solid understanding of backend architecture, distributed systems, and fundamental mathematical concepts like linear algebra and statistics.

Full description

We are looking for a highly skilled Software Engineer with strong expertise in Node.js, Generative AI, and modern AI application development to support enterprise Business Platforms and Risk & Compliance initiatives.

The ideal candidate will have hands-on experience building production-grade AI-powered applications and integrating Large Language Models (LLMs), APIs, and enterprise data sources. This role requires strong backend engineering capabilities, experience with GenAI frameworks and cloud-based AI services, and the ability to develop scalable, secure, and high-performance AI-enabled systems.

The successful candidate will work closely with cross-functional engineering teams to design and develop intelligent applications that leverage modern AI technologies while adhering to enterprise-grade engineering standards.

Key Responsibilities• Design, develop, and maintain scalable backend applications using Node.js and TypeScript.

  • Build production-grade AI-powered applications integrating LLMs, APIs, and enterprise data sources.
  • Develop and maintain RESTful APIs using Express.js.
  • Design and implement AI workflows using modern GenAI frameworks and orchestration tools.
  • Integrate cloud-based AI services from Azure and AWS platforms.
  • Build and optimize AI-enabled business applications for Risk & Compliance initiatives.
  • Develop robust prompt engineering strategies for enterprise AI use cases.
  • Implement scalable data processing pipelines and AI integrations.
  • Collaborate with product, engineering, and business teams to deliver AI-driven solutions.
  • Participate in code reviews and contribute to engineering best practices and architecture discussions.
  • Troubleshoot and optimize application performance, scalability, and reliability.
  • Ensure adherence to software engineering, security, and coding standards.

Required Technical SkillsBackend Technologies• Node.js

  • TypeScript
  • Express.js

Databases• PostgreSQL

  • MongoDB
  • Redis
  • Vector Databases

Testing Frameworks• Playwright

  • Jest

Cloud Platforms• Microsoft Azure

  • Amazon Web Services (AWS)

AI Platforms & Services• Azure OpenAI

  • OpenAI API
  • AWS Bedrock

AI Frameworks & Integrations• LangChain

  • LangGraph
  • Prompt Engineering
  • LLM Integrations
  • AI Model Orchestration
  • API Integrations

Required GenAI ExpertiseCandidates should have hands-on experience with:

  • Building production-grade Generative AI applications.
  • Integrating Large Language Models (LLMs) with enterprise applications.
  • Developing AI-powered workflows using LangChain and LangGraph.
  • Working with vector databases for semantic search and Retrieval-Augmented Generation (RAG) use cases.
  • Prompt engineering techniques for enterprise AI applications.
  • Designing scalable and secure AI-enabled systems.

Required Technical Competencies• Strong understanding of RESTful API design principles.

  • Experience developing scalable and secure backend architectures.
  • Strong understanding of distributed systems and modern software engineering practices.
  • Experience working with production-grade AI and cloud-native applications.
  • Familiarity with CI/CD and modern development workflows.
  • Excellent debugging, problem-solving, and performance optimization skills.

Required Academic KnowledgeCandidates should possess a good understanding of:

  • Linear Algebra
  • Probability
  • Statistics

These concepts are essential for understanding modern AI and machine learning systems and their practical enterprise applications.

Preferred Experience• Enterprise AI application development.

  • Risk & Compliance platforms.
  • Business platform engineering.
  • Cloud-native architectures.
  • Large-scale backend systems.
  • Modern AI and LLM ecosystems.

Required Competencies• Strong analytical and problem-solving skills.

  • Excellent communication and stakeholder management capabilities.
  • Ability to work effectively in Agile and cross-functional teams.
  • Strong ownership mindset and delivery excellence.
  • Quick learner with a passion for modern AI technologies and continuous innovation.
  • Ability to adapt to evolving business and technical requirements.

Preferred Domain Experience• Banking

  • Financial Services
  • Risk & Compliance Platforms
  • Enterprise Business Applications