AI Engineer - FinTech Automation, Equity & Flexible Work

SiFi - Simplified Financial Solutions Company; Riyadh; On-site; SAR 280,000 - 420,000; Full time

Job summary

SiFi, a fintech startup in Riyadh, is seeking an AI Engineer to join the Data & AI team and push AI-powered automation in corporate finance. You will own problems from prototype to production, working across the stack from LLM pipelines to backend infrastructure to internal tooling.

You will collaborate with Product, Engineering, Finance, and Operations to deliver AI features that impact how hundreds of companies manage money, including expense categorization, receipt reconciliation, and policy

Qualifications

• Hands-on production experience with LLMs and prompt design.
• Experience building end-to-end AI features for finance or similar data-sensitive domains.
• Comfort with ship-fast mindset and auditability requirements.

Responsibilities

• Design and ship AI-powered features end to end—from prompts to APIs and UI.
• Build AI infrastructure for LLM inference, retrieval-augmented generation, and data extraction.
• Develop autonomous agent workflows for finance ops like categorization and reconciliation.
• Collaborate with Data Engineering to ensure clean, trusted financial data.
• Create internal tooling to monitor model performance in production.
• Stay up-to-date with state-of-the-art techniques and apply where valuable.

Skills

LLM pipelines

Prompt design

RAG pipelines

Structured extraction

Agentic systems

Backend APIs

Cloud infrastructure

Tools

Python

FastAPI

LLM tooling

Job description

SiFi, a fintech startup in Riyadh, is seeking an AI Engineer to join the Data & AI team and push AI-powered automation in corporate finance. You will own problems from prototype to production, working across the stack from LLM pipelines to backend infrastructure to internal tooling.

You will collaborate with Product, Engineering, Finance, and Operations to deliver AI features that impact how hundreds of companies manage money, including expense categorization, receipt reconciliation, and policy