Large Language Model Experts in Austria
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Meet FRATCH Experts in Austria, who have recently used Large Language Model
Alexander P.
Last position:
Owner & Lecturer at Artellico / Own company for AI governance and data products
- Consulting and interim management at the intersection of IT operations and regulation
- Impact assessment and implementation planning for NISG 2026 and the EU AI Act, including risk management and reporting and evidence processes
- Training for governing bodies and employees on regulatory obligations
- Teaching assignments in Data & Information Management and Human-Machine Interaction at Hochschule Burgenland, since 2023
- Supervision of Master's theses and participation on examination boards
- Industry talks for businesses and educational institutions
- Design and development of data and AI products, platforms and pipelines
- Privacy-first architectures and Zero-Knowledge encryption, cloud-native on EU infrastructure
- Integration with bank account systems using SEPA direct debit mandates and message formats under ISO 20022 (pain.008, camt.053)
- MLOps and AIOps in live operations
- Own applications under my own brand: shared codebase, separate deployment for each target device
- AI-assisted software development (vibe-coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Professional publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- Professional publications on data sovereignty, cloud economics and industrial image processing
- AI governance / compliance: data quality, Responsible AI, EU AI Act readiness, risk classification, AI ethics
Thomas P.
Last position:
Change Manager / AI-driven Finance Transformation at Agrana
Organizational Change Management for the strategic setup of a hybrid GBS rollout as part of a global, AI-driven Finance Transformation. End-to-end management of the OCM architecture in a highly complex on-, near-, and offshore partner setup [IN, PL, RO]. Successful completion of Phase 1 (Initial Strategy) and strategic pausing by the Executive Board after the early disclosure of critical vendor-side OPEX risks
Systemic Baseline Assessment & Stakeholder Diagnostics: Evaluation of the global organization and analysis of the process landscape across 21 countries [AT, DE, CH, FR, UK, SI, RO, UA, RU, US, CD, CN, AR, MX, ZA, IN, JP] to precisely determine change requirements
Architecting the OCM Strategy & Master Roadmap: Independent development of a comprehensive, AI-centered Change Roadmap for end-to-end management of all change initiatives across every project phase
Data Quality & AI Agent Risk Mitigation: Auditing of Process Data Repositories (Celonis analysis); prevention of the ingestion of 58% synthetic training data to safeguard AI model reliability amid geopolitical supply chain tensions
GBS Vendor BAFO Triage & Contractual Commitment: Critical review of Tier-1 vendor pitches and contractual commitment to a reduced Non-STP rate (from 7% to 4%) to avoid extreme manual rework with a planned FTE reduction (-63%)
Executive Enablement & Board Alignment: Design of the GBS Transformation Executive Board Deck to strategically enable C-level executives and transparently present completely overlooked AI tokenization costs
Targeted Change Communications & Engagement: Design and development of audience-specific communication measures to align the highly diverse, globally distributed stakeholder network
Adoption Velocity & Resistance Measurement: Engineering of quantitative measurement tools (Pulse Check Survey) using Behavioral Dyads to identify resistance based on data and ensure sustainable success measurement
Results:
- Avoidance of disruptive misallocations: Stopping the ingestion of 58% synthetic AI-agent training data after discovering only 42% compatibility with existing processes, preventing critical GBS cascade errors
- Significant OPEX & effort reduction: Reduction of the Non-STP rate in Tier-1 vendor BAFOs from 7% to 4% alongside an impending 63% Finance-FTE reduction; avoidance of thousands of time-consuming manual correction processes
- 100% Delivery of the OCM architecture & ROI protection: Delivery of all OCM artifacts (Change Roadmap, Comms Plan, Executive Board Deck, Pulse Check Survey) and protection of ROI by identifying incalculable LLM runtime token costs
Chrisabel P.
Last position:
AI Systems & Product Strategy Expert at Webmeisterin
I build. I advise. I think in systems. After years leading digital transformation at scale — Accenture, BP, Lidl — I made a deliberate choice: trade platform dependency for structural independence. My focus is at the intersection of AI systems, product strategy, and venture thinking. I work with operators and founders who want to move fast without losing control — of their data, their stack, their direction.
Daniel S.
Last position:
AI Strategy & Use-Case Development at Umwelt Service Salzburg
- AI strategy concept and implementation roadmap for an energy consulting company.
- Use-case matrix with nine application scenarios (including funding research, chatbot, initial AI consulting, topic radar), implemented as reusable Claude Code skills.
- AI strategy, use-case analysis / Claude Code Skills / n8n.
Matthias K.
Last position:
Requirements Engineer & Business Analyst at Media Company
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
Manuel P.
Last position:
AI Engineer at Misumi Europe GmbH & Motius GmbH
- 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.
Roman M.
Last position:
Software Engineer at FSM Rechtsanwälte
- 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.
Christoph K.
Last position:
AI Project Manager at Logistics industry
- Project management for the introduction of an AI-supported email automation system for a logistics service provider
- Requirements analysis, stakeholder coordination, consulting, implementation support
Marcel S.
Last position:
Senior AI Engineer - Python at Insurance Company
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.
Shahram F.
Last position:
Senior Product Owner at Elderly Neighbour Watch
Delivery of a digital, non-profit neighborhood platform connecting older people with volunteers for practical support and social companionship. Responsibility for business analysis, requirements definition, platform evaluation and delivery of a locally scalable service solution, with a focus on AI-supported development, data-driven optimization and clear market positioning. Evaluation of several low-code/business platforms, including Odoo and Glide Apps, as well as assessment of monday.com as a CRM-related option, before selecting Glide Apps for implementation. Implementation of a non-native mobile and desktop application with Glide Apps and the website with WordPress. Responsibilities
- Gathering, analyzing and structuring business requirements for the product and service model
- Conducting market, target group and competitor analyses to position the offering
- Evaluating and selecting suitable low-code/business platforms for implementation
- Defining key user journeys, business processes and operational workflows for older people, volunteers and Administration
- Translating business requirements into requirements for profiles, task management, coordination, communication and notifications
- Supporting the implementation of the non-native mobile and desktop application in Glide Apps and the website in WordPress
- Preparing future AI-supported functions such as intelligent matching and data-driven optimization
- Ensuring compliance with GDPR requirements Results
- Successfully delivered digital support platform connecting older people with volunteers
- Solid foundation for market positioning through market, target group and competitor analyses
- Implemented functional non-native mobile and desktop application with Glide Apps and accompanying website with WordPress
- Created foundation for scaling and AI-based further development
Fabio G.
Last position:
IT Architect, Requirements Analyst and Consultant at CANCOM
- 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
Slavi S.
Last position:
Head of AI Enablement at REEVO Tech
- Architected enterprise AI strategy delivering 25% cost reduction through multi-LLM platform integration (Claude, OpenAI, Gemini) with intelligent routing and fallback optimization
- Drove operational excellence achieving 85% reduction in manual documentation and 3x faster campaign production through AI workflow automation and agent deployment across Slack and Microsoft Teams
- Established AI governance framework from ground up, implementing EU AI Act compliance, data redaction protocols, and safety filters aligned with DPIA standards
- Scaled AI adoption through structured onboarding programs, developing departmental workflows with secure access controls and comprehensive audit trails
- Implemented advanced RAG systems using Elasticsearch, Vertex AI, and Azure AI Foundry to improve knowledge access and output reliability
- Managed delivery through OKR framework coordinating cross-functional squads across 6-week project cycles to ensure strategic alignment and measurable results
René Z.
Last position:
DevSecOps & Kubernetes Engineer (Freelance) at mgm technology partners GmbH
Development of a Custom Jenkins Shared Library (Groovy)
Integration of security checks in CI/CD pipeline (Shift-Left Approach)
Automated vulnerability scanning and remediation workflows
GitOps-based deployments with ArgoCD
Semantic versioning automation with Git integration
Container lifecycle management (Build/Scan/Tag/Push)
ArgoCD webhook integration for event-driven deployments
Complete cluster automation with Ansible
Bare-metal Kubernetes installation from scratch
High-availability control plane setup
Unified deployment system for multi-application orchestration
Configuration management according to NIST SP 800-128
Host security: Linux hardening, SELinux/AppArmor
Network security: NetworkPolicies, micro-segmentation
Application security: RBAC, Pod Security Standards
Data security: Encryption at rest and in transit
Defense-in-depth principles
Certificate management with cert-manager
Secrets management with External Secrets Operator connected to Vault
Infrastructure monitoring with Checkmk
Prometheus/Grafana monitoring stack
Security event detection and logging
Automated health checks and incident response procedures
MetalLB load balancing for bare-metal
Nginx ingress controller with SSL passthrough
NetworkPolicies for security zones
Rook-Ceph distributed storage, CNI configuration (Weave Net)
Container & orchestration: Kubernetes (bare-metal), Docker, Helm
CI/CD & GitOps: Jenkins (Custom Shared Library), ArgoCD, Groovy
Automation: Ansible, Bash, Python
Security: nftables, RBAC, NetworkPolicies, cert-manager, Vault, Sealed Secrets
Monitoring: Checkmk, Prometheus, Grafana
Storage & networking: Rook-Ceph, MetalLB, Nginx Ingress, Calico
Collaboration: Jira, Confluence
OS: Debian, Ubuntu
Ulrike M.
Last position:
AI Trainer & Agentic AI Designer at Creating AI Daily
- AI workshops and training for marketing and specialist teams in medium-sized companies in the DACH region, in German and English, on site and remote
- Participants develop their own AI use cases and implement them directly in the workshop instead of just hearing theory
- Concept and orchestration of AI agents and automated workflows: research, market monitoring, content production, inquiry handling
- AI-supported brand and content production with Claude, ChatGPT and Microsoft Copilot, brand-consistent and with human approval
- Landing pages and websites in corporate design, built with Claude Code
- Image, video and voice with Midjourney, HeyGen, ElevenLabs, Adobe Firefly, Canva and CapCut
- More than 20 years of art direction as the foundation, so AI results have brand quality and do not look like AI
- Clients from industry, real estate and property management, as well as consulting
Zachery L.
Last position:
Fractional Director, Growth & Revenue | Strategic Advisor at Multi-Client Engagements
- Lead fractional growth and automation engagements across multiple companies, auditing, designing, and implementing AI-driven automations and agentic systems that create measurable commercial and operational impact with deterministic execution for complex business workflows.
- Audit AI readiness and ROI, then architect and deploy agentic systems that harden institutional knowledge and fix operational bottlenecks ensuring scalable growth and unimpeded strategic execution.
- Design commercial-ready multi-agentic architecture for orthopedic prior authorization workflows, shifting clinical decision-making from high-variance manual efforts to an auditable, deterministic clinical infrastructure.
- Implement Human-in-the-Loop (HITL) synthesis to ensure 100% medical authority while enabling up to 90% reduction in administrative time.
- Lead the migration of legacy marketing and sales functions into agent-first workflows, utilizing LLMs to synthesize internal data and external market signals for real-time go-to-market adjustment and champion talent development across the team.
Discover over 15,000 top freelancers
Statistics of experts using Large Language Model
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
2.4 years
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Manufacturing
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
92%
Master's degree or higher
64%
Doctorate
12%
Certifications per freelancer
3
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts in Austria using Large Language Model
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Large Language Model experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (93%)
- Banking and Finance (70%)
- Manufacturing (52%)
- Professional Services (52%)
- Healthcare (44%)
- Media and Entertainment (44%)
- Retail (44%)
- Energy (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it is
A Large Language Model is a machine learning system trained on extensive text and code to understand prompts and generate language. Companies use LLMs for conversational interfaces, document processing, search, summarisation, content workflows and software assistance. The technology can work with text, code, images or audio when combined with multimodal models.
What it builds
LLM specialists turn general-purpose models into useful business systems. They define the interaction, connect trusted data and add controls around generation.
- Customer and employee assistants
- Retrieval-augmented search and question answering
- Document extraction, classification and summarisation
- Content, code and workflow automation
- Multimodal applications for text, images or audio
Ecosystem and tooling
The work may involve OpenAI, Anthropic, Google Gemini, Meta Llama or open-source models served through Hugging Face. Common components include vector databases, embeddings, prompt templates, evaluation suites, orchestration libraries and API gateways. Strong specialists also understand Python, data pipelines, cloud services, observability and access control.
When to bring in expertise
Freelance support is useful when a team needs to validate an LLM use case, select a model or move a prototype into production. It is also valuable when answers must be grounded in private data, costs need control or outputs require traceability.
- A chatbot gives inconsistent or unsupported answers
- Internal documents are difficult to search
- A proof of concept needs production architecture
- Model quality and safety lack clear evaluation
What strong specialists deliver
Good professionals start with measurable user outcomes rather than prompt tricks. They choose the right model and context strategy, design fallbacks and test accuracy, latency, safety and data handling. They document assumptions and make the system maintainable for the in-house team.
In Austria, collaboration may combine remote delivery with on-site workshops. German-language requirements, regional data handling expectations and existing enterprise systems should be clarified early.
Delivery and quality
A reliable LLM project separates experimentation from dependable operation. Specialists establish representative test sets, monitor responses and review failure cases with domain experts. They also plan human review, version changes, permission boundaries and a route for users to report incorrect results.
The best fit depends on the task: a hosted model may speed up delivery, while an open model can offer more control over deployment and data. Either approach needs clear ownership, secure integration and a realistic plan for ongoing evaluation.
Frequently asked questions
Need clarity? These are the questions we hear most often about Large Language Model.
A Large Language Model can power assistants, semantic search, document analysis, summarisation, content workflows and code support. It is most useful when language is a central part of the process and the system can be connected to reliable business context.
An LLM generates and interprets language rather than following only fixed rules or matching exact keywords. It can handle varied requests and summarise information, but traditional software remains better for deterministic calculations and strict business rules. Search systems are often combined with an LLM to provide grounded answers.
A strong Large Language Model professional should understand APIs, Python, data preparation, embeddings, vector databases and cloud deployment. Security, evaluation design, prompt engineering and retrieval-augmented generation are also important for production work.
The right level of LLM experience depends on the risk and scope of the use case. A simple prototype may need prompt and API skills, while a customer-facing system needs proven work with evaluation, monitoring, privacy, integration and failure handling.
Yes, many Large Language Model projects can be delivered remotely through shared repositories, workshops and secure cloud environments. On-site sessions can still help with process discovery, stakeholder alignment and access to sensitive systems. German-language communication may matter when the users or source documents are local.
Ask for a clear evaluation method using representative prompts and documented success criteria. A capable LLM specialist should explain accuracy limits, unsupported-answer handling, data sources, security controls and how model changes will be monitored.
An open model can offer greater control over deployment, adaptation and data location, but it may require more infrastructure and operational expertise. A hosted model can shorten delivery and provide strong general capabilities. The decision should reflect data sensitivity, integration needs, quality targets and maintenance capacity.
A Large Language Model engagement often combines discovery, model selection, prompt or retrieval design, integration and evaluation. Freelancers should clarify access to data, language requirements, security constraints and who owns ongoing monitoring. Remote work is common, with occasional on-site collaboration where workshops or restricted systems require it.
The average hourly rate of freelancers in Austria who have used Large Language Model in their recent projects is 105 €, which corresponds to a daily rate of about 838 € based on an 8-hour working day.
Of the freelancers in Austria who have used Large Language Model in their recent projects, 92% hold at least a Bachelor's degree, 64% hold at least a Master's degree, and 12% hold a doctorate.
On average, freelancers in Austria who have used Large Language Model in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Austria who have used Large Language Model in their recent projects are German (100%), English (100%), and Spanish (26%).
The most common industries among freelancers in Austria who have used Large Language Model in their recent projects are Information Technology (93%), Banking and Finance (70%), and Manufacturing (52%).
The most common business areas among freelancers in Austria who have used Large Language Model in their recent projects are Information Technology (96%), Product Development (89%), and Business Intelligence (59%).
Main locations of FRATCH Experts, who have recently used Large Language Model
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Vienna Graz 
Vienna Countries:
- Germany
- Austria
- Switzerland
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FRATCH CEO
