
Rapyd
AI Software Engineer
- Permanent
- Dubai, United Arab Emirates
- Experience 5 - 10 yrs
- Urgent
Job expiry date: 11/12/2025
Job overview
Date posted
27/10/2025
Location
Dubai, United Arab Emirates
Salary
Undisclosed
Compensation
Comprehensive package
Experience
5 - 10 yrs
Seniority
Senior & Lead
Qualification
Bachelors degree
Expiration date
11/12/2025
Job description
Rapydâs AI Software Engineer role in Dubai focuses on designing, building, and scaling backend services and RESTful APIs to power AI-driven features within a unified global FinTech platform for payments, payouts, and financial technology. The position turns AI ideas into production-grade APIs and microservices, developing and iterating on LLM-based applications including context-aware pipelines with vector-store retrieval, and integrating generative models with external knowledge via retrieval-augmented generation (RAG). The engineer owns the full lifecycleâprototyping, evaluation, deployment, monitoring, and continuous iterationâdefining KPIs, running experiments, and optimizing systems based on metrics and data. The role requires hands-on work with embeddings, vector databases such as FAISS and Pinecone, and building and scaling data pipelines for LLM ingestion and retrieval, while staying current with the evolving LLM/agent ecosystem and rapidly applying new tools or protocols (e.g., MCP). Collaboration spans product, data, and engineering to translate ideas into robust, shippable systems, operating at the edge of whatâs possible with LLMs, RAG pipelines, and vector-based retrieval to automate workflows, elevate productivity, and make AI a reliable part of Rapydâs infrastructure.
Required skills
Key responsibilities
- Design, build, and scale backend services and RESTful APIs to power AI-driven features.
- Develop and iterate on LLM-based applications including context-aware pipelines with vector-store retrieval.
- Own the full lifecycle from prototyping and evaluation through deployment, monitoring, and continuous iteration.
- Define KPIs, run experiments, and optimize AI systems based on metrics and real data.
- Collaborate across product, data, and engineering to translate ideas into robust, shippable systems.
- Stay current with the LLM/agent ecosystem and rapidly apply new tools or protocols such as MCP.
Experience & skills
- 5+ years of professional software development experience with a strong backend focus.
- Experience with advanced LLM workflows including prompt engineering, inference optimization, fine-tuning, and evaluation.
- Demonstrated experience integrating generative models with external knowledge via RAG or similar patterns.
- Practical knowledge of embeddings and vector databases such as FAISS or Pinecone.
- Experience building and scaling data pipelines for LLM ingestion and retrieval.
- Bonus: Previous work with agent frameworks or context protocols.
- Bonus: Experience with Agile practices and a habit of staying on top of AI research and tooling.
- Bonus: Hands-on experience designing and building microservices architectures.