Senior AI Engineer

About Commercial Bank of Qatar

Established in 1975 and headquartered in Doha, Commercial Bank plays a pivotal role in Qatar's economic landscape by delivering a variety of personal, corporate, government, international, and investment banking services.

We champion employee empowerment, offering pathways for professional growth and skill advancement.

By becoming part of our team, you'll engage with a culture that nurtures innovation, promotes a healthy work-life balance, and supports your maximum potential.

Join us in transforming the future of banking.

Role Overview

The Senior AI Engineer leads the architecture, development, and deployment of sophisticated Agentic AI systems and enterprise AI platforms within our Data & AI Lab. This senior position demands considerable proficiency in AI engineering, cloud solutions, integration methodologies, and financial services expertise.

This role combines hands-on technical implementation with leadership, ensuring AI applications meet production standards, scalability requirements, and adhere to banking regulations.

Key Responsibilities

• Design and implement advanced Agentic AI solutions including autonomous workflows, multi-agent setups, and orchestrated AI ecosystems.
• Establish architecture and best practices for AI agent development and Model Context Protocol (MCP) integrations.
• Innovate AI capabilities by assessing emerging technologies and steering adoption.
• Lead AI platform creation focusing on vector stores, embedding pipelines, and retrieval mechanisms.
• Develop scalable frameworks for document parsing, processing, and extraction of metadata to support enterprise knowledge management.
• Define API and integration standards for widespread AI services across the bank.
• Architect scalable, secure, and cost-efficient AI cloud infrastructures on Azure and Google Cloud Platform (GCP).
• Implement event-driven architectures leveraging Kafka for real-time AI and streaming applications.
• Define infrastructure norms for model serving on OpenShift/Kubernetes, incorporating monitoring and MLOps procedures.
• Offer technical mentorship, lead design and code reviews, and guide adherence to software engineering best practices including CI/CD and knowledge sharing.
• Collaborate with enterprise architecture and IT units to ensure AI aligns with organizational technology and data strategies.
• Engage stakeholders to transform business needs into technical solutions while managing communications with senior leadership and governance bodies.
• Contribute to AI governance ensuring compliance with data policies, ethics, and banking regulations, including setting SLAs and monitoring AI solution health.

Required Expertise & Competencies

• Profound knowledge of large language models (LLMs), embedding techniques, and generative AI frameworks.
• Experience with AI orchestration frameworks, multi-agent systems, and complex agent development.
• Expertise with vector databases, Retrieval-Augmented Generation (RAG) architectures, and knowledge retrieval methodologies.
• Proficiency with deep learning frameworks such as TensorFlow and PyTorch; familiar with ML deployment tools like MLflow and TFX.
• Comprehensive ML lifecycle management including model monitoring.
• Advanced software engineering skills in Python and AI/ML frameworks including LangChain, LlamaIndex, and Semantic Kernel or equivalents.
• Experience in API design, microservices, event-driven system architectures, and advanced SQL usage (stored procedures, window functions, recursive queries).
• Familiarity with version control tools and CI/CD pipeline best practices using GitHub or GitLab.
• Strong mastery of cloud platforms (Azure/GCP), object storage systems (S3, GCS, Azure Blob Storage).
• Advanced capabilities with Kafka, Apache Spark, and workflow orchestration tools such as Airflow and Apache NiFi.
• Hands-on experience with container technologies and orchestration such as Docker and Kubernetes (OpenShift).
• Expertise in MLOps including versioning, model monitoring, and management.
• Demonstrated leadership in mentoring and managing technical initiatives; excellent stakeholder engagement and communication including data visualization and reporting.

Educational & Professional Background

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or aligned disciplines.
• Over seven years in software engineering, with at least four years dedicated to AI/ML implementations.
• Proven leadership in delivering AI applications within production environments.
• Extensive experience with cloud platforms (Azure or GCP), container orchestration (OpenShift/Kubernetes), and enterprise AI integrations.
• Mandatory prior exposure to banking or financial services industry.
• Preferred background in regulatory compliance, data governance, and security specific to financial sectors.
• Relevant professional certifications such as Azure AI Engineer or GCP ML Engineer are highly desirable.

Why Choose Commercial Bank?

• Recognized as Best Digital Bank and Best Mobile Banking App in the Middle East for 2024 by respected global financial bodies.
• Work within an innovative, digital-first environment using cutting-edge technologies.
• Access global partnership opportunities and international exposure.
• Prioritize well-being and work-life balance in a supportive culture.
• Competitive salary and benefits reward dedication and achievement.
• Strong commitment to diversity, equity, and inclusion, appreciating diverse perspectives.

Additional Information

Commercial Bank values your application; however, only selected candidates will be contacted for further recruitment stages.

This posting is informational; the bank retains the right to amend or remove it without notice at any time.