AI Engineer
Role Overview
The AI Engineer designs, develops, and deploys agentic AI solutions and AI-enabled platforms within the Data & AI Lab.
The role builds AI infrastructure with cloud integrations, vector stores, document-processing pipelines, and real-time data streaming.
The engineer works with AI Product Owners, Data Scientists, and engineers to deliver scalable, maintainable production AI for banking operations and customer-facing applications.
Key Skills for This Role
Full Job Posting
About Commercial Bank of Qatar
Commercial Bank was founded in 1975 and is headquartered in Doha, providing personal, business, government, international, and investment services.
Role overview
The AI Engineer designs, develops, and deploys agentic AI solutions and AI-enabled platforms within the Data & AI Lab.
The role builds AI infrastructure with cloud integrations, vector stores, document-processing pipelines, and real-time data streaming.
The engineer works with AI Product Owners, Data Scientists, and engineers to deliver scalable, maintainable production AI for banking operations and customer-facing applications.
Key accountabilities
- Design agentic AI workflows, multi-agent systems, orchestration patterns, and integrations with MCP or similar frameworks.
- Build AI pipelines, vector stores, embedding pipelines, retrieval systems, and document-processing and metadata-extraction pipelines for RAG.
- Develop APIs and integration layers and connect AI services with banking systems and applications.
- Deploy cloud-based AI solutions; implement Kafka streaming; manage model serving on OpenShift/Kubernetes, monitoring, and performance.
- Contribute to Agile delivery, sprint planning, code reviews, testing, documentation, and CI/CD; uphold security, governance, and regulatory standards.
Key competencies
- AI/ML competencies include LLMs, embedding models, generative AI, agent development, orchestration frameworks, vector databases, and RAG.
- Software competencies include advanced Python, AI/ML libraries, REST APIs, microservices, advanced SQL, and Git.
- Cloud and data competencies include Azure or GCP, object storage, Kafka, Airflow or Apache NiFi, Docker, Kubernetes/OpenShift, Spark, and MLOps.
- The role calls for cross-functional collaboration and clear communication of technical concepts to non-technical stakeholders, as well as Agile/Scrum or Kanban experience.
Qualifications and experience
- The supplied description ends mid-sentence at the start of the qualifications section; no degree or experience requirement can be confirmed from the available text.
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