GenAI Engineer (m/f/d)

Halian; Riyadh; On-site; SAR 200,000 - 300,000; Full time

Job summary

A premier bank seeks an AI specialist to join their innovation team in Riyadh. This role involves exploring and implementing generative AI applications, improving financial regulatory processes, and developing synthetic datasets for compliance testing. The ideal candidate will have over 5 years of experience in AI/ML, especially in conversational AI and generative models. Proficiency in Python and cloud services like Google Cloud and Azure is essential. This position offers opportunities to drive innovative projects within the financial sector.

Qualifications

• Minimum 5 years in AI/ML roles, specialized in GenAI solutions.
• Experience in designing and developing conversational AI systems.
• Strong proficiency in building and fine-tuning generative AI models.
• Familiarity with AML typologies and fraud detection frameworks.

Responsibilities

• Explore and implement generative AI applications for Suptech.
• Collaborate with stakeholders for AI-driven solutions.
• Lead development activities using ML techniques.
• Code solutions following best practices.
• Design AI-driven synthetic financial datasets.

Skills

Generative AI solutions

Conversational AI systems

Synthetic data generation

ML pipelines

Prompt engineering

Python programming

Tools

Google Cloud Services

Azure

Docker

CI/CD pipelines

Job description

About the Role

Join our AI innovation team at a premier bank to continuously conduct a range of technology exploration, development, prototyping, and technology transfer work, relevant to the financial sector. This includes analysis, identification, and implementation of potential use‑cases that leverage emerging technologies.

Key Responsibilities

• Explore and implement generative AI applications for Suptech, creating synthetic data environments to test AML/CTF controls without direct inspection, reducing supervision costs and improving coverage.
• Collaborate with regulatory stakeholders to guide and inform broader efforts to transform supervisory functions using AI‑driven solutions.
• Work on design, development, and implementation of innovative projects and use‑cases that employ emerging technologies, notably data science, analytics, AI, GenAI, and NLP in the financial sector, in cooperation with internal and external stakeholders.
• Work with the project team—business analysts, solution architects, and developers—to understand solution requirements.
• Lead development activities such as:
  • Selecting features and building and optimizing classifiers using ML techniques.
  • Data mining with state‑of‑the‑art methods.
  • Processing, cleansing, and verifying data integrity for analysis.
  • Creating automated anomaly detection systems and continuously tracking performance.
• Deliver innovation hub prototypes, MVPs, technical reports, and effective outputs.
• Support solution architect in documenting low‑level design and understanding software requirements.
• Code solutions following best practices and documenting code.
• Recommend and plan installation of new systems or modifications of existing systems.
• Define testing strategies and perform prototype and MVP testing to ensure flawless performance.
• Design AI‑driven synthetic financial datasets that replicate real‑world transactional behaviors for compliance stress testing.
• Embed AML typologies, financial crime red flags, and money laundering patterns into synthetic transaction flows.
• Apply adversarial ML to stress‑test compliance detection algorithms, identifying blind spots.
• Establish benchmarks for AML detection performance (false‑positive/negative rates, detection lag, operational efficiency) and develop scoring mechanisms for compliance system resilience.
• Conduct controlled regulatory stress tests to assess how compliance teams and automated systems handle high‑risk financial crime scenarios.
• Design and develop conversational AI systems and intelligent chatbots for enterprise banking applications.
• Build and operationalize generative AI models aligned with business objectives and regulatory requirements.
• Implement Retrieval‑Augmented Generation (RAG) systems and agentic workflows to enhance contextual relevance and task automation.
• Develop and optimize prompt engineering strategies for maximum LLM performance.
• Build robust, scalable ML pipelines and deploy AI solutions in production environments.

Required Qualifications

• Minimum 5 years in AI/ML roles, specialized in GenAI solutions.
• Demonstrated experience in designing and developing conversational AI systems and intelligent chatbots for enterprise use cases.
• Strong proficiency in building and fine‑tuning generative AI models aligned with specific business objectives.
• Experience in synthetic data generation for financial or compliance applications and familiarity with AML typologies and fraud detection frameworks is highly desirable.
• Exposure to Suptech or Regtech initiatives and understanding of supervisory technology trends is a plus.

Technical Skills

• Hands‑on expertise in implementing Retrieval‑Augmented Generation (RAG) and agentic workflows to enhance contextual relevance and task automation.
• Skilled in prompt engineering, iterative design, and testing to optimize LLM performance.
• Proven ability to build robust, scalable ML pipelines using platforms.
• Solid understanding of Google Cloud Services and development environments.
• Experience deploying and operationalizing Azure Foundation Models and Azure OpenAI services within production environments.
• Familiarity with containerization and DevOps practices, including Docker and CI/CD pipelines.
• Advanced programming skills in Python, focusing on high‑quality maintainable code for AI/ML applications.
• Knowledge of adversarial machine learning techniques, compliance stress‑testing methodologies, and Suptech use cases is a strong advantage.