Quant AI Engineer

Overview

Role Overview

Ai & Quantitative Model Development

• Develop machine learning and quantitative models for forecasting, risk analytics, pricing, anomaly detection, and market intelligence.
• Design and implement predictive models using statistical, machine learning, and deep learning techniques.
• Optimize model accuracy, reliability, and performance across production environments.
• Build frameworks for model evaluation, experimentation, and continuous improvement.

Ai Platform Engineering

• Build scalable machine learning pipelines for model training, deployment, monitoring, and lifecycle management.
• Develop APIs, services, and infrastructure that expose AI and quantitative capabilities to business applications.
• Implement MLOps practices including model versioning, monitoring, governance, and automated deployment.
• Ensure high availability, scalability, and observability of AI systems.

Llm & Agentic Ai Solutions

• Design and implement LLM-powered applications for research automation, knowledge extraction, decision support, and operational workflows.
• Develop Retrieval-Augmented Generation (RAG) architectures using internal and external datasets.
• Build AI agents and workflow orchestration solutions that automate complex business processes.
• Evaluate emerging AI technologies and integrate them into production systems where appropriate.

Data & Systems Integration

• Integrate AI solutions with trading platforms, market data feeds, risk systems, and enterprise applications.
• Work with structured and unstructured datasets across real-time and batch processing environments.
• Ensure data quality, security, governance, and regulatory compliance across AI initiatives.

Technical Requirements

• Strong software engineering experience using Python.
• Experience with machine learning frameworks including PyTorch, TensorFlow, Scikit-learn, and XGBoost.
• Strong understanding of machine learning engineering, model deployment, and MLOps practices.
• Experience building production-grade AI and machine learning systems.
• Knowledge of LLM frameworks such as LangChain, LangGraph, LlamaIndex, OpenAI APIs, or AWS Bedrock.
• Experience building RAG systems, vector database solutions, and AI agents.
• Experience with SQL, Spark, Kafka, Docker, Kubernetes, and CI/CD pipelines.
• Familiarity with AWS, Azure, or GCP cloud platforms.

Qualifications

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Quantitative Finance, or a related discipline.
• 5–10 years of experience in AI engineering, machine learning engineering, quantitative development, or software engineering.
• Experience developing production systems within financial services, fintech, brokerage, capital markets, crypto, or other high-performance environments is highly desirable.
• Understanding of trading systems, market data, pricing, risk management, and quantitative finance concepts is preferred.
• Strong analytical, engineering, and problem-solving capabilities.'

Why Join Us?

• Work with an industry-leading global financial institution.
• Competitive salary and comprehensive employee benefits.
• Opportunities for professional growth and career advancement.
• Collaborative, inclusive, and dynamic work environment.
• Commitment to innovation and professional excellence.
• *Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.*