Senior AI Solution Architect

About the role

The Senior AI Solution Architect will design AI/ML solution patterns that integrate with an existing data platform. The role focuses on building scalable, real‑time and batch inference pipelines using modern data technologies. You will work closely with data architects, ML engineers, and client stakeholders to ensure seamless integration.

Key responsibilities

• Design end‑to‑end AI/ML solution architecture that plugs into the Iceberg/Trino/Spark lakehouse.
• Define patterns for batch inference (via Spark) and real‑time inference (via Kafka streaming).
• Architect the integration between Jupyter Enterprise Gateway‑based development environments and production inference infrastructure.
• Evaluate and select ML serving, feature‑engineering, and model‑lifecycle tooling appropriate for the platform.
• Partner with the Data Architect to ensure AI/ML workloads respect core data platform SLAs and resource allocation.
• Define reference architectures and reusable patterns for common AI use cases.
• Set standards for model governance, monitoring, and explainability.
• Present architectural recommendations to technical teams and client leadership.

Required profile

• 8+ years of software/data engineering experience, with at least 5 years in ML/AI solution architecture.
• Hands‑on experience designing both batch and real‑time inference architectures using Spark and Kafka.
• Familiarity with multi‑tenant notebook infrastructure such as Jupyter Enterprise Gateway.
• Strong understanding of integrating AI/ML workloads with a lakehouse environment (Iceberg, Trino, Spark) without disrupting core operations.
• Experience with major ML frameworks (PyTorch or TensorFlow) at an architectural level.
• Excellent stakeholder communication skills to bridge data platforms, ML engineering, and client leadership.

Required skills

• Jupyter Enterprise Gateway
• Kafka
• Spark
• Iceberg
• Trino
• PyTorch
• TensorFlow