AI Engineer

sifiapp; Riyadh; On-site; SAR 149,981 - 224,971; Full time

Benefits offered by this job

Competitive salary

Equity

Flexible working environment

Job summary

sifiapp in Riyadh Region is seeking an experienced AI Engineer to join their Data & AI team. This role requires designing and shipping AI-powered features, maintaining AI infrastructure, and developing workflows for automating finance operations. Candidates should have strong engineering fundamentals, hands-on experience with LLMs, and the ability to work with high-stakes financial data. The benefits include flexible working conditions, competitive salary, and equity in a dynamic startup environment.

Qualifications

• Strong engineering fundamentals across backend systems, APIs, and cloud infrastructure.
• Hands-on experience building with LLMs in production, including prompt design, RAG pipelines.
• Comfortable working with financial or compliance-sensitive data.

Responsibilities

• Design and ship AI-powered features end to end.
• Build and maintain AI infrastructure for LLM inference.
• Develop autonomous agent workflows for finance operations.

Job description

Job Description

About Us

SiFi is building the next-generation Office of the CFO — a corporate expense management platform that gives accounting teams seamless control over company spending. We let companies issue cards with precise spending restrictions, automate expense workflows, and close books faster. As we scale, AI is becoming core to how we deliver financial intelligence, automation, and trust to our customers.

We are a small, high-ownership team. Everyone builds, everyone ships, and everyone is accountable for outcomes.

About the Role

We are looking for an AI Engineer to join our Data & AI team and help us bring AI-powered automation into the heart of corporate finance. You will work across the full stack — from LLM pipelines and agent workflows to the backend infrastructure and internal tooling that makes them production-ready.

This is a hands‑on, end‑to‑end role. You will own problems from prototype to production — in a domain where financial data is structured, high‑stakes, and unforgiving. Getting it wrong has real consequences for real companies. You will work closely with Product, Engineering, Finance, and Operations to build AI features that make a direct impact on how hundreds of companies manage money.

What You’ll Do

• Design and ship AI‑powered features end to end — from prompt engineering and model integration to backend APIs and frontend surfaces.
• Build and maintain AI infrastructure for LLM inference, retrieval‑augmented generation (RAG), and structured data extraction from financial documents.
• Develop autonomous agent workflows that automate finance operations such as expense categorization, receipt reconciliation, and policy enforcement.
• Partner with the Data Engineering team to ensure AI systems are grounded in clean, trusted, and well‑modeled financial data.
• Build internal tooling and evaluation frameworks to measure, monitor, and improve model performance in production.
• Stay close to the state of the art and bring relevant techniques — fine‑tuning, tool use, multi‑agent orchestration — into SiFi’s stack where they create real value.

Requirements

• Strong engineering fundamentals across backend systems, APIs, and cloud infrastructure — you are comfortable owning the full lifecycle of a production AI feature.
• Hands‑on experience building with LLMs in production, including prompt design, RAG pipelines, structured extraction, or Agentic systems.
• Comfort working with financial or compliance‑sensitive data, where correctness and audit ability matter.
• A bias toward shipping — you move fast, make pragmatic trade offs, and iterate based on real‑world feedback.
• Low ego, high ownership: you are as comfortable debugging an edge case as you are proposing a new system architecture.

Nice to Have

• Familiarity with fin‑tech or expense management domains.
• Prior work at an early‑stage startup or in a small, high‑velocity team.

Benefits

Why SiFi

• Work on AI problems that are genuinely hard: financial data is structured, high‑stakes, and unforgiving — the opposite of toy problems.
• Own meaningful surface area from day one on a lean team where your decisions shape the product.
• Competitive salary and equity.
• Flexible working environment.
• A front‑row seat to building a category‑defining fin‑tech from the ground up.