Senior AI Solutions Architect – Financial Services Architecture

Poland-based opportunity with a hybrid work model.

As a Senior AI Solutions Architect – Financial Services Architecture, you will design scalable, secure, high-performance AI architectures that enable advanced analytics, predictive modeling, and intelligent automation across critical banking operations. You will collaborate with data engineers, AI scientists, and business stakeholders to integrate AI solutions into enterprise infrastructure and align technology with business strategy.

Quick Facts

• Hybrid work model
• Financial-services AI architecture role
• Focus on enterprise AI, analytics, predictive modeling, and intelligent automation

Responsibilities

• Design and implement end-to-end AI solution architectures across data, model, and infrastructure layers.
• Collaborate with cross-functional teams to define technical requirements and ensure system scalability.
• Evaluate and select AI frameworks, tools, and cloud platforms suited to business needs.
• Oversee model integration, deployment, and lifecycle management in production environments.
• Ensure compliance with security, data governance, and regulatory standards.
• Support data and MLOps teams in building robust data pipelines and CI/CD processes for AI.
• Provide technical leadership in AI solution design, proof-of-concepts, and technology assessments.
• Develop architecture blueprints, documentation, and best practices for AI initiatives.
• Identify opportunities to optimize performance and reduce operational costs through automation.
• Guide and mentor engineering teams in AI system design and implementation.

Requirements

• At least 5 years of experience in software or data engineering, including 3+ years in AI/ML architecture.
• Proven track record of designing enterprise-scale AI systems using cloud platforms, including AWS or Azure.
• Strong understanding of MLOps practices, CI/CD pipelines, and containerization using Docker and Kubernetes.
• Experience with big-data technologies, including Spark, Kafka, and Hadoop, as well as modern data-lake architectures.
• Deep knowledge of machine-learning frameworks, including TensorFlow, PyTorch, and Scikit-Learn.
• Understanding of data governance, security, and compliance in financial institutions.
• Ability to translate business objectives into technical architecture and implementation plans.
• Familiarity with API design, microservices, and event-driven systems.
• Excellent communication and stakeholder-management skills.
• Fluency in spoken and written Polish and English.
• Existing legal right to work in the European Union.