
Snr AI & ML Engineer
At a Glance
- Category
- 💻 Technology
- Level
- Mid-Level
- Experience
- 7+ years
- Type
- Full-time
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𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀
𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟮𝟬𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟰𝟬𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟮𝟬-𝟰𝟬 𝗟𝗣𝗔)
Experience: 7+ yrs
Location: Abu Dhabi, United Arab Emirates
Job Type: Full-time
We are seeking a Senior AI/ML Engineer to design, develop, and deploy production-grade AI and machine learning solutions for financial services use cases. This is a hands-on role for an experienced professional with strong expertise in Python, Machine Learning, Generative AI, LLMs, RAG, Agentic AI, and Data Engineering.
The ideal candidate will be comfortable transforming complex business and financial requirements into scalable AI-powered applications. You will work closely with finance, quantitative, technology, and business teams to develop practical solutions across areas such as risk, credit, compliance, treasury, markets, and financial reporting.
Requirements
Key Responsibilities
- Design, develop, and deploy AI/ML and Generative AI solutions for financial services use cases.
- Build LLM applications, RAG pipelines, AI agents, document intelligence solutions, and workflow automation tools.
- Develop scalable Python-based APIs, model services, dashboards, and data pipelines.
- Work with financial datasets, including transaction data, credit data, market data, financial statements, and unstructured documents.
- Support AI solutions across risk management, credit, treasury, compliance, markets, corporate banking, and management reporting.
- Prototype innovative AI solutions rapidly and transform successful prototypes into production-grade applications.
- Design and implement solutions using technologies such as Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, FastAPI, Flask, Streamlit, LangChain, LangGraph, LlamaIndex, vector databases, embeddings, and RAG.
- Build and integrate cloud-native solutions using Azure, AWS, or GCP, along with Docker, Kubernetes, Git, and CI/CD practices.
- Collaborate with finance and quantitative teams to translate complex methodologies into practical software solutions.
- Implement appropriate testing, logging, monitoring, security, and basic MLOps practices.
- Work with cross-functional teams to understand business requirements and deliver scalable solutions.
- Mentor junior engineers, developers, and analysts on coding standards, modelling practices, testing, and deployment.
What Makes You a Great Fit
- 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.
- Exposure to banking, fintech, payments, insurance, asset management, consulting, or capital markets is highly valuable.
- Knowledge of financial use cases such as credit risk, fraud, KYC, treasury, trading, portfolio analytics, regulatory reporting, or financial document processing is an advantage.
- A practical, delivery-focused mindset with the ability to build solutions quickly and continuously improve them for production use.
Requirements
- •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
- •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 and unstructured financial data
- •Experience with cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes)
- •Mentoring junior engineers
Nice to Have
- •Experience with FastAPI, Flask, Streamlit, LangChain, LangGraph, LlamaIndex
- •Knowledge of CI/CD practices
- •Collaboration with finance and quantitative teams
- •Implementing testing, logging, monitoring, security, and basic MLOps practices
- •PMP certification
Responsibilities
- •Design, develop, and deploy AI/ML and Generative AI solutions for financial services use cases
- •Build LLM applications, RAG pipelines, AI agents, document intelligence solutions, and workflow automation tools
- •Develop scalable Python-based APIs, model services, dashboards, and data pipelines
- •Work with financial datasets
- •Support AI solutions across various financial domains
- •Prototype innovative AI solutions rapidly and transform prototypes into production-grade applications
- •Design and implement solutions using specified technologies
- •Build and integrate cloud-native solutions
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