Large Language Model Expert in Vienna
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Meet FRATCH Experts in Vienna, 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.
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.
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
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.
Maximilian G.
Last position:
Solo Developer / Founder at InvAPI
- Privacy-first, stateless e-invoice API providing AI-powered extraction, bidirectional format conversion (UBL/CII/ZUGFeRD), batch processing, and validation for German/Austrian e-invoice compliance
- Technologies: Nuxt 4, Vue 3, Nitro, TypeScript, Cloudflare (D1, R2), Stripe, OAuth, AI/LLM integration
Anton L.
Last position:
CISO & Interim DPO at Finmatics GmbH
- Built the company’s entire security function from zero to ISO-aligned, audit-ready operation (ISO 27001, GDPR, NIS2).
- Delivered enterprise-grade security posture enabling regulated customer onboarding and due-diligence success.
- Embedded automated security controls (SAST, DAST, secrets, vuln scanning) into CI/CD for a growing SaaS engineering team, removing security as a deployment bottleneck.
- Cut third-party risk exposure by ~70% by replacing manual vendor reviews with an automated, LLM-driven risk scoring and approval pipeline.
- Led board-level security, customer audits, and live incident response.
Christian M.
Last position:
Senior Feature Engineer - Banking at start.me app e.U.
- Requirements engineering & business analysis
- Architecture responsibility for core banking extensions
- Interface modeling for third-party systems (TiGital, ESA, ÖNB)
- AML, KYC & payment reporting
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
1.9 years
Positions per freelancer
12
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Project Management, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
75%
Doctorate
13%
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 Vienna 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 Vienna 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 (88%)
- Banking and Finance (71%)
- Professional Services (65%)
- Manufacturing (59%)
- Retail (53%)
- Healthcare (47%)
- Media and Entertainment (47%)
- Transportation (41%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Large Language Models do
Large Language Models, often called LLMs, process and generate human language from patterns learned across extensive training data. Companies use them for conversational assistants, document analysis, content workflows, semantic search, code support and multilingual interfaces. Their value depends on connecting language capability to a clearly defined business process.
Core project applications
LLM specialists turn broad model capabilities into controlled products and workflows:
- Build customer support assistants grounded in internal knowledge
- Extract, classify and summarise information from business documents
- Create retrieval-augmented generation pipelines with citations
- Add natural-language search and question answering to applications
- Evaluate prompts, responses, safety behaviour and production quality
Ecosystem and tooling
Work around an LLM can include OpenAI models, Anthropic Claude, Google Gemini, Meta Llama and open-weight models hosted in a private environment. Specialists commonly use Python, TypeScript, API gateways, vector databases, embedding models and orchestration tools such as LangChain or LlamaIndex. They also connect model services with data warehouses, cloud infrastructure, observability and existing application interfaces.
When freelance expertise helps
Companies often bring in external specialists when an experiment must become a dependable product, when proprietary documents need secure retrieval, or when model output is inconsistent. Expertise is also useful during model selection, prompt and evaluation design, fine-tuning decisions, cost and latency reviews, and the integration of access controls. In Vienna, teams may need both remote delivery and focused on-site workshops, with clear communication across German- and English-speaking stakeholders.
Skills that matter in delivery
Strong professionals understand language models without treating them as a complete solution. They define success criteria, select suitable data, design reliable prompts and retrieval flows, and test failure cases before release. They can work with APIs and open models, manage context and token limits, protect sensitive information, and explain trade-offs to product, legal and engineering teams. Production work also requires monitoring, fallback logic and human review where the risk demands it.
Choosing the right specialist
Look for evidence of complete LLM systems rather than isolated demos. A strong portfolio should show the source data, retrieval or fine-tuning approach, evaluation method and safeguards around inaccurate or unsafe output. Ask how the specialist handles changing model behaviour, confidential content, multilingual requirements and difficult user questions. The best fit combines practical software delivery with disciplined testing and a clear understanding of your domain.
Frequently asked questions
Questions about Large Language Model? Start with the answers below.
Large Language Models are used to generate and transform text, answer questions, summarise documents, extract structured information and support natural-language search. They can also power assistants, content workflows and software features when connected to trusted data and suitable controls.
An LLM can interpret varied language and produce flexible responses, while traditional search is usually better for precise retrieval and rules-based software is easier to predict. Many robust products combine all three: search or retrieval supplies grounded information, rules enforce constraints, and the model handles language interaction.
A capable Large Language Model specialist should understand Python or TypeScript, APIs, data processing, vector databases, cloud services and application integration. Useful adjacent knowledge includes prompt design, retrieval-augmented generation, evaluation, privacy, security and observability.
The required depth depends on the deliverable. A prototype may need focused model and integration knowledge, while a production system requires experience with evaluation, data governance, monitoring, access control and failure handling. Ask for examples similar to your data, users and risk level rather than relying on a generic experience label.
LLMs are well suited to remote collaboration because development, evaluation and deployment use shared repositories and cloud environments. On-site sessions in Vienna can still help with discovery, data workshops and stakeholder alignment, especially when German- and English-speaking teams need to agree on terminology and review standards.
An LLM accessed through an API can reduce infrastructure work and provide rapid access to advanced capabilities. Hosting an open model may offer more control over data, deployment and customization, but it adds responsibility for hardware, updates, scaling, security and performance evaluation.
Large Language Models usually benefit from retrieval-augmented generation when answers must reflect changing or private documents. Fine-tuning is more appropriate for adapting behaviour, format or task patterns that cannot be addressed through instructions and retrieved context alone. A specialist should test both options against representative cases.
A strong LLM professional explains how outputs are evaluated, how incorrect answers are detected and how sensitive data is protected. Review a relevant delivery example, ask to see the testing approach, and discuss fallback behaviour, monitoring, model changes and the limits the specialist would communicate to users.
The average hourly rate of freelancers in Vienna, Austria who have used Large Language Model in their recent projects is 111 €, which corresponds to a daily rate of about 889 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Large Language Model in their recent projects, 100% hold at least a Bachelor's degree, 75% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Vienna, Austria who have used Large Language Model in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 1.9 years.
The most common languages among freelancers in Vienna, Austria who have used Large Language Model in their recent projects are German (100%), English (100%), and Spanish (35%).
The most common industries among freelancers in Vienna, Austria who have used Large Language Model in their recent projects are Information Technology (88%), Banking and Finance (71%), and Professional Services (65%).
The most common business areas among freelancers in Vienna, Austria who have used Large Language Model in their recent projects are Information Technology (94%), Product Development (88%), and Business Intelligence (71%).
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.
Countries:
Vienna 
Graz Request a free demo
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FRATCH CEO
