Snr AI & ML Engineer
$2,000,000–$4,000,000 year
On-siteAbu Dhabi, Abu Dhabi, United Arab Emirates
Job Summary
Design, develop, and deploy production-grade AI/ML and Generative AI solutions for financial services use cases, including building LLM applications, RAG pipelines, AI agents, and workflow automation tools. Develop scalable Python-based APIs, model services, dashboards, and data pipelines while working with financial datasets such as transaction, credit, and market data. Support AI solutions across risk management, credit, treasury, compliance, markets, and corporate banking by collaborating with finance and quantitative teams to translate complex methodologies into practical software. Prototype innovative AI solutions rapidly and transform them into production-grade applications using technologies like Azure, AWS, or GCP, along with Docker, Kubernetes, and CI/CD practices. Mentor junior engineers on coding standards and deployment while implementing testing, logging, monitoring, and MLOps.
Required Qualifications
- 7+ years of experience in AI/ML Engineering, Data Science, Software Engineering, or Analytics Engineering
- Strong hands-on expertise in Python and modern machine learning frameworks
- Proven experience building and deploying real-world AI/ML applications rather than working exclusively with notebooks or prototypes
- Strong understanding of LLMs, Generative AI, RAG, agentic workflows, NLP, embeddings, vector databases, or document intelligence
- Experience developing APIs, data pipelines, dashboards, and production-grade model services
- Familiarity with SQL, structured databases, cloud platforms, containers, CI/CD, testing, and deployment practices
- Strong problem-solving and analytical skills with the ability to work through ambiguous business challenges
- Ability to communicate effectively with both technical teams and finance/business stakeholders
- A practical, delivery-focused mindset with the ability to build solutions quickly and continuously improve them for production use
Desired Qualifications
- Exposure to banking, fintech, payments, insurance, asset management, consulting, or capital markets
- Knowledge of financial use cases such as credit risk, fraud, KYC, treasury, trading, portfolio analytics, regulatory reporting, or financial document processing
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