Anton Rösler-AI-Engineer
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Experience
AI-Engineer
Publicly traded company, industrial safety technology
- Designed and implemented the agent-based AI architecture for a company-wide platform to securely deploy LLM-based agents
- Designed and implemented end-to-end RAG pipelines from multiple sources: document preprocessing, chunking strategies for different document types, embeddings, retrieval with re-ranking, and robust prompt orchestration
- Developed a modular context engineering framework with skill architecture, context isolation, and dynamic resource management; human-in-the-loop control for enterprise tool integrations
- Built the CI/CD pipeline, testing strategy, tracing on the software side as well as automated LLM and agent evaluations, red team testing and tracing, and handed over to a reproducible production environment (ISO27001 and SOC2 compliant)
Software Developer for Machine Learning Use Cases
Bosch Engineering
- Designed, implemented, and deployed ML inference and data pipelines on Azure and AWS as part of a multi-tenant, event-driven web service processing petabytes of multi-sensor data for automotive customers worldwide
- Designed and built a RAG pipeline for multi-sensor measurement data on Elasticsearch with a multi-stage retrieval architecture: hybrid retrieval (vector + BM25), hierarchical metadata filtering by domain dimensions, query routing, and cross-encoder re-ranking of top candidates
- Built an idempotent ingestion pipeline for the RAG data store (>1M entries/day) with Delta Live Tables and Auto Loader; schema evolution for varying sensor formats, orchestrated via Databricks Workflows
- Built an Azure Databricks lakehouse for over 10 TB of time-series data, enabling unified analytics and ML experiments for 5+ engineering teams; created PySpark ETL workflows for feature extraction and versioned dataset management via Delta Lake and Unity Catalog
Industry Experience
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Experienced in Automotive and Manufacturing.
Business Area Experience
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Experienced in Information Technology, Product Development, and Quality Assurance.
Summary
I am an AI Solutions Engineer with extensive experience in designing and building cloud systems and data architectures. I have been heavily involved in the full lifecycle of sophisticated ML pipelines and cloud infrastructures, leveraging Databricks, AWS, and Azure. My work includes creating robust agent-based AI architectures and end-to-end RAG pipelines that process large-scale, multi-sensor data in dynamic environments.
I specialize in building scalable systems with a focus on agent context and harness engineering, modular design, and automation. I have developed secure deployment processes and effective CI/CD pipelines while ensuring high performance and compliance across various industries. This background enables me to deliver efficient, reliable solutions in demanding and evolving technical landscapes.
Skills
Specialization: Data Engineering · Ai Systems · Ml Pipelines · Production & Automated Deployment Of Ai, Data & Ml Systems · Workflow Automation
Architecture: Event-Driven · Serverless · Microservices · Multi-Account Strategies · Security & Governance · Mlops
Ai/Ml: Langchain · Langgraph · Langflow · Bedrock · Openai · Anthropic · Pytorch · Scikit-Learn · N8n
Stack: Python · Terraform · Aws Cdk · Docker · Github Actions
Cloud Services: Aws (Including) Lambda · Ecs · S3 · Sqs · Athena · Glue · Bedrock · Api Gateway · Batch · Dynamodb · Aurora · Sagemaker
Cloud Services: Azure (Including) Functions · App Services · Container Apps · Storage · Queues · Aks · Batch · Entra · Azure Ml · Cosmos Db
Data: Databricks · Delta Lake & Lakehouse · Pyspark · Sql · Nosql · Parquet · Vector Databases · Graph Databases
Languages
Education
Frankfurt University of Applied Sciences
Bachelor of Science · Engineering Business Information Systems · Frankfurt, Germany · 1.0
Certifications & licenses
AWS: AI Practitioner
AWS
AWS: Data Engineer (Associate)
AWS
AWS: GenAI Developer (professional)
AWS
AWS: Solutions Architect (Associate)
AWS
IBM: Professional Certificate Deep Learning
IBM
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