Docker Experts in Vienna

• Analysis of existing work, information and decision-making processes.

• Identification and prioritization of suitable use cases for AI agents.

• Elicitation of functional and non-functional requirements.

• Design of collaboration between users and AI agents, including control and escalation mechanisms.

• Support for the implementation of the AI agents and adapted keyboard hardware.

• Business target vision for the AI-first transformation.

• Structured and prioritized requirements for implementation.

• Defined roles, interactions and control points between people and AI agents.

• Preparation for the gradual automation of productive work processes.

Techstack: AI agents, LLMs, agent orchestration, RAG, APIs, automation, hardware

Cyber Trust Austria Silver Certification

• Led application and implementation of the Cyber Trust Austria Silver label (KSV1870 Cyber Risk A-Rating; 25 validated controls)
• Mapped and fulfilled requirements covering risk management, incident response, access control, vulnerability and penetration testing, BCM, and supply-chain security, aligned with ISO/IEC 27001/27002 control themes and NIS 2 / NISG 2026 expectations
• Coordinated stakeholders, compiled audit evidence, and completed KSV1870 validation

Refactoring and improving core APIs; implementing client change requests. Setting up metrics, traces, and logs monitoring infrastructure to support operations. Designing GitOps deployment and infrastructure as code. Applications and systems configuration in ArgoCD and Openshift. Confluence documentation of design, approach, and solution. Tech Stack: Java 8 & 21, Spring framework, JSP, JavaScript, Bash scripts, SQL, Grafana Stack, OpenTelemetry, Docker, DB2, Maven, Kubernetes Kompose.

Senior Expert / Program Manager

IT Services

• Management of internal projects for infrastructure modernization: setup and maintenance of test environments that realistically replicate complex customer networks.
• Resource coordination: planning server capacities and cloud resources for automated test runs.
• Implementation of CI/CD pipelines to integrate automated tests into the build process.
• Evaluation of performance bottlenecks through load testing (NeoLoad/JMeter) to ensure scalability.

Tools / Technologies: Jenkins, Docker, GIT, ButBucket, NeoLoad, Azure

• Designed and built a next-generation NLP platform to accelerate sales-driven customer service through intelligent request analysis and routing, reducing average customer query response time by 30%.
• Architected a hybrid NLP system combining Large Language Models (LLMs) with traditional NLP pipelines for robust, explainable results.
• Developed request classification and routing mechanisms to accelerate customer support teams in handling customer queries faster and more accurately.
• Optimized LLM based data extraction and classification with context engineering.
• Integrated the platform into customer service processes, reducing response times and enhancing workforce efficiency.

• Develop AWS-based components connecting Python backend services to React/TypeScript frontends.
• Improve database queries and application workflows for document processing and screening.
• Evaluate LLM retrieval and document-review workflows as part of the product stack.

• Took Dawnguard from initial product concept to a launched MVP within two months, building the backend platform and reducing cloud-environment scan times from approximately 40 minutes to under two minutes across 70 accounts.
• Designed and built the core resource discovery engine for Azure and AWS, enabling the frontend to visualise complex cloud environments and the AI to evaluate architectural patterns.
• Engineered distributed APIs and dynamic Cosmos DB schemas to support rapidly evolving product requirements and variable cloud-environment structures.
• Built the architecture-generation engine to support clients with 100+ cloud accounts and dynamically generate complete architectures containing approximately 25,000 resources.
• Developed custom data-generation tools that enabled the AI and frontend teams to simulate and test large-scale cloud architectures.
• Delivered backend features end to end by working with AI, frontend, and business stakeholders from technical design through implementation and testing.

Tech: AWS (Glue, Lambda, Redshift), Airflow, PostgreSQL, Python, PySpark, Metabase, Power BI

Delivered: Analytics-Ready Data Models • Legacy SQL to Cloud ETL Migration • Dynamic Pricing Engine

• Owned and evolved the company data warehouse end-to-end — from ingestion to transformation to analytics-ready dimensional data models on AWS Redshift.
• Collaborated with Analysts, Data Scientists, and business stakeholders to deliver scalable dimensional data models that enable self-serve analytics and streamline dashboarding in Metabase and Power BI.
• Architected end-to-end ETL/ELT pipelines on AWS (Glue, Lambda, Redshift) using Python and PySpark, orchestrated with Apache Airflow (MWAA) for reliability and observability.
• Defined and enforced data quality standards and governance practices across pipelines and the core data layer.
• Led migration of legacy SQL infrastructure into scalable AWS Glue pipelines with distributed PySpark processing, eliminating bottlenecks and reducing downtime.
• Developed a dynamic pricing engine applying automated promotional discounts based on occupancy rates, competitor pricing, and location performance tiers.
• Designed schema mappings to ingest MongoDB data into structured relational systems (Redshift/PostgreSQL).

Project Tech Stack: Python, AWS, Azure, FastAPI, openai, pandas, unittest/pymock

Achievements:

• Engineered automated data extraction pipelines to transform complex Excel datasets into structured formats via LLM-driven workflows.
• Architected a generative slide-deck engine that translates natural language prompts into formatted presentation assets.
• Integrated advanced LLM capabilities with the OpenAI Response API, implementing sophisticated tool-calling and structured output logic.
• Developed and containerized scalable backend microservice using FastAPI, Docker, and OpenShift to host and serve agentic skills.

Implementation and operation of OpenShift / Kubernetes solutions for customers, focusing on aspects such as storage, virtualization, security, logging, monitoring, and high availability. Support with application containerization and modernization.

• Responsible for managing GMP-Critical systems
• Leading team of 20 professionals
• Vendor management with €15 M annual budget

• Teaching & presenting
• Communication
• Effectively communicate complex technical topics to non-technical audiences through lectures
• Guided non-technical students from zero knowledge to confidently understanding and applying algorithms to achieve business outcomes

• Supports CANCOM customers in migrating legacy on-prem systems to Microsoft Fabric and Microsoft Foundry
• Takes over and stabilizes existing solutions after a short handover
• Business analysis and requirements engineering for migration to a new cloud environment
• Optimization of machine learning models for feature extraction and customer profiling
• Ensures data protection and compliance
• Leads the migration of on-prem systems to Microsoft Fabric
• Designs new AI platforms for clients
• Tests the integration of chatbots for document intelligence with Microsoft Foundry, including requirements analysis, implementation, validation, and client communication

• Develop a concept for the analysis of sensor data.
• Assess implementation options, products, and pricing in Azure.
• Present and advocate the solution concept to the client.
• Implement an ETL pipeline for processing sensor data.
• Integrate BI solutions with the data repository.
• Provide documentation and support for end users.