AI Solution Architect

We are seeking an AI Solution Architect to translate complex banking business needs into scalable, secure enterprise AI system blueprints. This role owns end-to-end technical delivery from high-level design through production deployment while ensuring every solution aligns with the demands of a highly regulated financial IT landscape.

Key Responsibilities

• Design high-level and low-level architectures for banking AI applications
• Securely integrate modern AI applications with core banking systems and databases
• Evaluate and select optimal LLMs, vector stores, and machine learning platforms
• Ensure enterprise-grade high availability, low latency, and system scalability
• Embed financial regulatory compliance, risk mitigation, and data privacy into every design decision
• Partner with engineering, security, and platform teams through the full delivery lifecycle

8+ years in enterprise IT, including 3+ years architecting AI solutions specifically within banking/financial services

Hands-on experience with AI & data platforms: DataRobot, SAS Enterprise Guide, and open-source LLM frameworks

Strong grounding in architecture patterns: microservices, API gateways, event-driven architecture, secure banking cloud landing zones

CI/CD & MLOps proficiency: GitLab CI/CD, Docker, Kubernetes, MLflow, automated model testing frameworks

Advanced Python skills Pandas, NumPy, Matplotlib, Seaborn, LangChain, LlamaIndex

Strong communication skills to translate technical architecture into business-relevant terms for stakeholders

Why Join Us

• Architect enterprise-scale AI solutions inside a live banking transformation program
• Own technical decisions from blueprint to production real build authority, not just advisory
• Work at the intersection of cutting-edge AI and strict financial-sector compliance
• Be part of a forward-looking organization driving AI-led transformation in the region

8+ years in enterprise IT, including 3+ years architecting AI solutions specifically within banking/financial services

Hands-on experience with AI & data platforms: DataRobot, SAS Enterprise Guide, and open-source LLM frameworks

Strong grounding in architecture patterns: microservices, API gateways, event-driven architecture, secure banking cloud landing zones

CI/CD & MLOps proficiency: GitLab CI/CD, Docker, Kubernetes, MLflow, automated model testing frameworks

Advanced Python skills Pandas, NumPy, Matplotlib, Seaborn, LangChain, LlamaIndex

Strong communication skills to translate technical architecture into business-relevant terms for stakeholders