AI Product & Research Engineer

Capital Com SV Investments Limited; Dubai; On-site; AED 120,000 - 200,000; Full time

Job summary

A leading trading platform in Dubai is seeking an AI Engineer to join their newly formed AI department. The role involves prompt engineering, rapid prototyping, and integrating LLMs. Candidates should have a Master’s degree in AI or Computer Science and proficiency in Python. A passion for innovative AI solutions and excellent collaboration skills are essential. Join us for an exciting opportunity to impact the future of trading technology!

Qualifications

• Hands-on experience integrating LLM APIs (e.g. OpenAI, Hugging Face).
• Practical experience fine-tuning LLMs.
• Strong communication skills for framing AI solutions.

Responsibilities

• Craft, iterate, and optimize prompts for AI APIs.
• Implement retrieval-augmented workflows.
• Create interactive AI demos for feedback.

Skills

Prompt Engineering & Orchestration

Python expertise

Rapid Prototyping

MLOps

Cross-Functional Collaboration

Education

Master’s degree in AI and/or Computer Science

Tools

Docker

Kubernetes

FastAPI

Streamlit

LangChain

Job description

We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.

We’re spinning up a brand-new AI department and need a first‑on‑the‑ground engineer who can turn wild LLM ideas into working demos overnight, teach everyone around you why automation matters, and have fun doing it.

If you can ship Python or TypeScript prototypes, keep reading.

Responsibilities

• Prompt Engineering & Orchestration: Craft, iterate, and optimize prompts for APIs (OpenAI, Cohere, Anthropic). Build multi‑step “chains” using LangChain, LlamaIndex, or custom controllers. Develop and maintain AI microservices using Docker, Kubernetes, and FastAPI, ensuring smooth model serving and error handling.
• Vector Search & Retrieval: Implement retrieval‑augmented workflows: ingest documents, index embeddings (Pinecone, FAISS, Weaviate), and build similarity search features.
• Rapid Prototyping: Create interactive AI demos and proofs‑of‑concept with Streamlit, Gradio, orNext.jsfor stakeholder feedback.
• MLOps & Deployment: Implement CI/CD pipelines (e.g., GitLab Actions, Apache Airflow), experiment tracking (MLflow), and model monitoring for reliable production workflows.
• Cross‑Functional Collaboration: Participate in code reviews, architectural discussions, and sprint planning to deliver features end‑to‑end.

Requirements

• Master’s degree in AI and/or Computer Science.
• Hands‑on experience integrating LLM APIs (e.g. OpenAI, Hugging Face Inference).
• Practical experience fine‑tuning LLMs via OpenAI, HuggingFace or similar APIs.
• Strong proficiency in Python.
• Deep expertise in prompt engineering and tooling like LangChain or LlamaIndex.
• Proficiency with vector databases (Pinecone, FAISS, Weaviate) and document embedding pipelines.
• Proven rapid‑prototyping skills using Streamlit or equivalent frameworks for UI demos.
• Familiarity with containerization (Docker) and at least one orchestration/deployment platform.
• Excellent communication and ability to frame AI solutions in business terms.

Nice‑to‑have

• Familiarity with database systems (PostgreSQL, MongoDB) and caching layers (Redis).
• Open‑source contributions or published AI demos.
• Understanding of cost‑optimization, monitoring for LLM usage and model‑API trade‑offs.
• Familiarity with prompt engineering best practices and “vibe‑coding” tools (e.g., GitHub Copilot, Cursor IDE).
• Willingness to travel occasionally for team offsites or workshops.