// data & ai platform architect
Roland Utz
I architect and build enterprise data platforms and production AI systems — from streaming pipelines to LLM applications — for banking, telecom, energy, and industrial clients.
what i do
Architecture, hands-on engineering,
and technical leadership.
Physicist by training, engineer by trade. Fifteen-plus years as an independent contractor delivering large-scale data and machine-learning systems to enterprise standards of governance, compliance, and scale.
01 / data-platform-engineering
Data Platform Engineering
End-to-end pipelines and cloud big-data platforms at enterprise scale — streaming, warehousing, and governance built to survive production.
Spark · Kafka · Flink · Snowflake · Airflow
02 / generative-ai-llm-systems
Generative AI & LLM Systems
Production NLP, deep learning, and LLM applications — RAG platforms, model selection, fine-tuning, and evaluation strategies that ground answers in facts.
PyTorch · Transformers · vLLM · Milvus · Qdrant
03 / distributed-systems-cloud
Distributed Systems & Cloud
Cloud-native architectures across Azure, AWS, and GCP — Kubernetes, high-throughput messaging, and migrations off legacy on-prem ecosystems.
Azure · AWS · GCP · Kubernetes · Docker
selected work
Systems that shipped.
Enterprise Software Vendor
Enterprise RAG Platform
Greenfield Retrieval-Augmented Generation platform, from concept through MVP: ingestion, embeddings, vector search, and LLM orchestration across enterprise knowledge sources.
Python · PyTorch · vLLM
Major German Bank
Big Data Platform & Pipelines
Distributed Spark pipelines for the bank’s next-generation big data platform, with the technical evaluation that established Spark as its core compute engine.
Spark · Scala · Hadoop
European Telecom Group
Cloud Big Data Migration
Migration of a legacy on-premises Cloudera ecosystem to a cloud-native Azure architecture for high-volume telecom streams, including a custom Spark geospatial library.
Azure · Kafka · Kubernetes
Industrial SMB
IIoT Anomaly Detection
Sensor analytics and anomaly detection for industrial IoT, designed, productionized, and cost-optimized on AWS.
Python · TensorFlow · AWS
from the blog
Notes from the field.
August 16, 2026
Hybrid Retrieval and Reranking: The Part Where We Actually Build It
Part 2 of the RAG Architecture Series. Chunking, BM25 analyzers, fusion weights, cross encoders, and the mechanism behind the part number example I left dangling last time.
read
August 4, 2026
Which RAG architecture should you choose?
A 2026 decision guide for the people who sign off on the architecture and own the budget, not the ones writing the retrieval loop.
read