Large Language Model Experts in Austria
to build smarter products with vetted, available freelancersHire experts who design LLM applications, connect GPT models to business data and improve retrieval, evaluation and prompt workflows. FRATCH matches you quickly and precisely with vetted, available freelancers suited to your project.
Meet FRATCH Experts in Austria, who have recently used Large Language Model
Alexander P.
Last position:
Owner & Lecturer at Own company for AI governance and data products, Vienna
- Consulting and interim management at the interface between IT operations and regulation
- Impact analysis 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
- Lectures in Data & Information Management and Human-Machine Interaction at University of Applied Sciences Burgenland, since 2023
- Supervision of master’s theses and participation in the examination board
- Presentations for business 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
- MLOps and AIOps in live operations
- Own applications under own brand: shared codebase, separate delivery for each target device
- AI-assisted software development (vibe coding), complete agentic pipelines, code generation, implementation, automated testing, CI/CD and release cycles
- Publications on the EU AI Act, NIS2, DORA, CRA and CER as an integrated governance system
- 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
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.
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.
Daniel S.
Last position:
AI Automation in E-Commerce at Looops
- AI automation roadmap for a D2C/B2B e-commerce company.
- Customer service bot with RAG over support tickets and product data, OCR pipeline for incoming invoices with writeback to Business Central, lead gen and posting automation.
- Deterministic n8n workflows with EU-hosted models.
- n8n, RAG / Mistral, Qwen/BGE embeddings / Business Central API, HubSpot, Shopify / Scaleway, S3 / Claude Code, OpenCode.
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.
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.
Christoph K.
Last position:
AI project lead at Logistics industry
- Project lead for the introduction of an AI-supported email automation system for a logistics service provider
- Requirements analysis, stakeholder coordination, consulting, implementation support
Shahram F.
Last position:
Senior Product Owner at Elderly Neighbour Watch
Delivered a digital, non-profit neighborhood platform to connect older adults with volunteers for practical support and social companionship. Responsible for business analysis, requirement definition, platform evaluation and delivery of a locally scalable service solution focusing on AI-driven enhancements, data-based optimization and clear market positioning. Evaluated several low-code/business platforms including Odoo and Glide Apps and assessed monday.com as a CRM-like option before selecting Glide Apps for implementation. Implemented a non-native mobile and desktop application with Glide Apps and the web presence with WordPress. Tasks
- 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 core user journeys, business processes and operational workflows for older adults, volunteers and administration
- Translating business requirements into functional requirements for profiles, task management, coordination, communication and notifications
- Guiding the implementation of the non-native mobile and desktop application in Glide Apps as well as the web presence in WordPress
- Preparing the business side for future AI-powered features such as intelligent matching and data-based optimization
- Ensuring compliance with GDPR requirements Results
- Successfully delivered digital support platform connecting older adults with volunteers
- Solid foundation for market positioning through market, target group and competitor analyses
- Delivered a functional non-native mobile and desktop application with Glide Apps and a supporting web presence with WordPress
- Established 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
Thomas B.
Last position:
Agile Coach, Scrum-Master at ÖBB (Infra)
- Challenge: poor project results and team performance, very poor work environment
- Solution: introduction of agile planning processes, teaching agile principles within the SAFe framework
- Innovation: consistent use of agile methods; introduction of requirements engineering, story writing
- Leadership: interface with the board, program management Opel Europe, GM USA and international markets
- Result: most productive team in the ART; increased planning accuracy to over 85%
- Team size: 10
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
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.
David M.
Last position:
Senior Technical Consultant at BMW Group
- Architecture and development of enterprise React 19 based documentation platform for automotive software systems
- Full-stack implementation of visualization tools & interactive diagram viewers
- Performance optimization initiatives including virtual rendering for 10,000+ node trees and Web Worker-based search functionality
- Designed and implemented modular plugin architecture enabling extensible document rendering system
- Technical consultation on Git-based architecture-as-code workflows and modern design patterns
- Ownership of critical features from design through deployment, collaborating with cross-functional enterprise teams
Armin F.
Last position:
Head of AI & Data Science at Ascent DACH
- Lead architect for AI and ML projects including GenAI, LLM-based apps and forecasting solutions
- Guided customers through solution scoping, architecture design, and PoCs across various industries (Pharma, Insurance, Logistics, FMCG)
- Delivered production ML pipelines using Azure ML, MLflow, and MLOps best practices
- Responsible for effort estimation, delivery and staffing of 5 – 10 projects simultaneously
- Hiring manager for the data science and AI team and responsible for creating the technological offering and roadmap in the AI & Data Science space
- Built and scaled the AI/Data Science service offering from scratch to a high 6-figure annual revenue with 30+ successful deliveries and 20+ clients
- Regular speaker at AI and data science conferences and academic institutions
Discover over 15,000 top freelancers
Statistics of experts using Large Language Model
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
2.2 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, Project Management, Business Intelligence
Bachelor's degree or higher
95%
Master's degree or higher
71%
Doctorate
14%
Certifications per freelancer
2
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Austria are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge 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 19 Sep 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 (92%)
- Banking and Finance (75%)
- Manufacturing (50%)
- Professional Services (50%)
- Healthcare (42%)
- Education (33%)
- Energy (33%)
- Media and Entertainment (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What LLMs do
A Large Language Model, or LLM, processes and generates natural language from patterns learned across large text collections. Companies use it for conversational assistants, document search, content workflows, summarisation, classification and software interfaces. The model alone is rarely the complete product: useful results depend on data, context, controls and evaluation.
Applications and outputs
LLM specialists turn language models into reliable business features and internal tools. Common deliverables include:
- Customer support and knowledge assistants
- Retrieval-augmented generation for private documents
- Structured extraction from contracts, emails and reports
- Summarisation, drafting and multilingual workflows
- Natural-language interfaces for software and data
Ecosystem and tooling
The ecosystem includes model providers such as OpenAI, Anthropic and Google, open-weight models, embedding services and vector databases. Professionals work with APIs, Python or TypeScript, orchestration frameworks, evaluation suites, prompt versioning and observability tools. They also connect models to identity systems, business applications and secure data pipelines.
When expertise matters
Companies bring in freelance LLM expertise when a proof of concept must become a dependable product, or when an existing assistant produces inconsistent answers. Specialists can select an appropriate model, design retrieval and tool use, manage context limits, control access to sensitive data and create evaluation sets. In Austria, collaboration may involve German-language content, local teams and remote delivery across an international organisation.
What strong professionals deliver
Strong professionals understand both model behaviour and the surrounding system. They separate instructions, retrieved evidence and user input, reduce unsupported claims and test edge cases before release. They can explain trade-offs between hosted APIs and self-managed models, document data flows and build monitoring around quality, latency, cost and safety without treating any single metric as proof of success.
Signs of a good fit
Look for evidence that a specialist has handled production constraints, not only prompt experiments. Useful signals include:
- Clear evaluation methods tied to business outcomes
- Experience with RAG, embeddings and vector search
- Secure integration with APIs, permissions and private data
- Practical handling of hallucinations and model changes
- Clear documentation for users and technical teams
A strong fit asks precise questions about source data, users, failure modes and acceptance criteria. They can work independently while keeping stakeholders involved, whether the project is on-site in Austria or fully remote.
Frequently asked questions
Need clarity? These are the questions we hear most often about Large Language Model.
A Large Language Model can support customer conversations, search private knowledge, summarise documents and extract structured information. It can also provide a natural-language interface to business software when connected to approved tools and data.
An LLM handles flexible language and can generate or transform text, while traditional software is more predictable for fixed rules and calculations. Search retrieves relevant sources; an LLM can explain or combine them, but it needs grounding and checks to avoid unsupported answers.
A Large Language Model specialist should understand APIs, data preparation, embeddings, vector databases, retrieval-augmented generation and evaluation. Security, prompt design, cloud integration and observability are also important when the model becomes part of a production system.
The right level depends on the risk, data sensitivity and integration depth of the project. A Large Language Model proof of concept may need focused application expertise, while a customer-facing system benefits from a professional who has handled evaluation, access controls, monitoring and changing model behaviour.
Yes. LLM work is often suitable for remote collaboration because model configuration, data pipelines and evaluation can be managed through shared repositories and cloud environments. On-site sessions can still help with discovery, stakeholder interviews and workshops, especially when German-language processes are involved.
A GPT model can offer convenient hosted access and strong general capabilities, while an open-weight model may provide more control over deployment and data handling. The choice depends on privacy requirements, language quality, operational capacity, integration needs and the evaluation results for the actual use case.
Ask a Large Language Model professional to show how they define success, test factuality and handle sensitive or ambiguous input. Good answers cover representative evaluation data, source citations or grounding, fallback behaviour, monitoring and clear trade-offs rather than relying on impressive demonstrations alone.
An LLM specialist should clarify the users, source data, permitted actions, languages, security boundaries and acceptance criteria. They should also confirm who owns model and prompt changes, how failures are reviewed and whether the work covers a prototype, a production release or ongoing improvement.
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 841 € based on an 8-hour working day.
Of the freelancers in Austria who have used Large Language Model in their recent projects, 95% hold at least a Bachelor's degree, 71% hold at least a Master's degree, and 14% hold a doctorate.
On average, freelancers in Austria who have used Large Language Model in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 2.2 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 (25%).
The most common industries among freelancers in Austria who have used Large Language Model in their recent projects are Information Technology (92%), Banking and Finance (75%), and Manufacturing (50%).
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 (88%), and Business Intelligence (63%).
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
Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
Would you rather directly get in touch?
We always have the time for a call or email!
Philipp Thomaschewski
FRATCH CEO
