Generative AI Experts in Switzerland
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Meet FRATCH Experts in Switzerland, who have recently used Generative AI
Stefan K.
Last position:
Projectmanager at IMG
Consultant for Digitalisation, Process Optimisation and System Integration, working in direct coordination with the Managing Director.
Responsible for the operational steering of a digital transformation initiative focused on process analysis, system integration, automation and structured service processes. Translation of business requirements into practical solutions based on SmartBrix/Odoo and connected communication and third-party systems.
Key areas:
- Structuring and optimisation of property management and customer service processes
- Product Ownership and Business Analysis
- System integration across SmartBrix/Odoo, Microsoft 365, VoIP and WhatsApp Business
- Coordination of external software and technology providers
- Development of testing, approval and quality assurance processes
- Use of AI for process and knowledge support
- Documentation, governance and risk management
- Transparent reporting of project progress, risks and decision requirements to management
Matthias S.
Last position:
Lecturer in Software Management at GraubĂĽnden University of Applied Sciences
- Design and delivery of the university module “Software Management” in the Bachelor’s degree program in Artificial Intelligence in Software Engineering
- Teaching software project management, project organization, stakeholder management, risk and quality management, and agile and hybrid project management
- Coverage of release planning, cut-over, go-live, handover to operations, and the operational impact of technical decisions
- Combining methodological foundations with experience from software development, customer projects, delivery, release management, testing, and IT operations
- Use of AI in software and project management
Methods and tools: Software project management, HERMES, PRINCE2, Scrum, Kanban, hybrid approaches, requirements engineering, risk and quality management, release management, test management, Moodle
Caroline Z.
Last position:
Support & Consulting in the Digital Transformation Environment at Schweizerische Mobiliar
via AgonPro AG
- Review and optimization of training materials, guides and documentation in the SAFe environment
- Structured and user-oriented preparation of complex content
- Critical analysis of existing solutions and development of specific improvement proposals
- Contributing to AI topics in the context of training and the introduction of artificial intelligence
Chris W.
Last position:
Senior Product / UX Designer at NOUMENA DIGITAL
- Designed services, interfaces and workflows for tokenized-finance and digital-asset ecosystems, including a MiCA-regulated stablecoin platform.
- Worked directly with product, engineering and stakeholders to translate business, regulatory, privacy and technical requirements into usable product experiences.
Charles S.
Last position:
Data Delivery Lead at Westpac
- Owned and managed the product roadmap and backlog for the Consumer Banker reporting framework, prioritising features and driving iterative delivery of banker scorecards and network performance reporting in an agile environment.
- Developed and iterated portfolio financial reporting on a weekly cadence based on stakeholder feedback, replacing manual PowerPoint packs and saving the program hours of effort weekly.
- Integrated Generative AI (MS Copilot) to automate data lineage documentation across a large legacy codebase, eliminating est. 6 months of analyst effort and accelerating data governance outcomes.
- Led a unified data delivery approach and standards across five UNITE initiatives (~CHF 115m portfolio) supporting consolidation of legacy systems into the Digital Banker platform.
- Led cross-functional delivery team of 3 while also drawing on BA and DA talent pools, coordinating analytical resource across workstreams to accelerate data, reporting & governance outcomes.
Ralf R.
Last position:
Infrastructure-as-Code Transformation Architect at ODDO BHF
Responsible for designing and delivering a company-wide, comprehensive Infrastructure-as-Code (IaC) transformation in a regulated banking environment.
Conducted an assessment of the current infrastructure, processes, tools, teams, ways of working and skill profiles as a basis for the target architecture and a PDO (Product-Driven Organization)
Defined a tailored, audit-ready Everything-as-Code infrastructure (including governance, security and compliance)
Built a comprehensive IaC operating model, integrating and transforming internal teams
Designed standardised, reusable Terraform modules for infrastructure and platform services
Integrated secrets management, PKI and Encryption-as-a-Service to secure critical VMware and Kubernetes platform components and stored data
Implemented the platform in line with regulatory requirements (DORA, BaFin, ACPR, CRA), with a focus on auditability and traceability
The initiative provides the foundation for standardised, automated and audit-ready infrastructure, reduces manual intervention and enables scalable, traceable delivery of IT resources in a banking environment.
Élodie M.
Last position:
Senior Academic Assistant (Research & Teaching) at University of Lausanne – Section of History and Aesthetics of Cinema
- Academic research, critical analysis and information synthesis
- University teaching and content evaluation
- Source verification and archival research
- Scholarly writing, editing and structured feedback
- Evaluation of complex written and audiovisual material
- Research project development and coordination
Milan S.
Last position:
Cloud Architect & DevOps at Avaloq
- Main cloud solution architect on a banking SaaS offering hosted in Azure.
- Fully automated the Azure infrastructure in Terraform.
- Reduced cloud costs by 50%.
- Responded to incidents, found root-causes and closed with post-mortems.
Malik O.
Last position:
AI Scientist at SQPS
- Intelligent Document Processing Engine with OCR & Computer Vision: Architected the end-to-end AI pipeline at the core of the SQPS GenAI document-processing product, which turns scanned paper and PDF batches into organised, searchable documents, combining image pre-processing, OCR and layout analysis for mixed-quality scans. Technologies: Python, OpenCV, Tesseract / PaddleOCR, PyTorch, FastAPI
- Automatic Document Splitting & Classification: Developed models that detect where one document ends and the next begins inside a single multi-document scan, and classify each one by type (invoices, contracts, letters, reports) to enable fully automated filing. Technologies: Python, PyTorch, scikit-learn, Hugging Face Transformers
- Information Extraction & Intelligent File Naming with LLMs: Implemented an LLM-based GenAI extraction system that reads dates, names and reference numbers from unstructured documents and uses them to generate consistent, rule-based file names, with configurable naming conventions per organisation. Technologies: Python, LangChain, OpenAI, SentenceTransformers, SQL
Christian B.
Last position:
5G Campus Product Advisor Telco at German railway group
- Definition of a product concept and end to end solution delivery (turnkey) for a Digital Efficiency Hub for Railway Maintenance based on 5G campus networks. Integration of various hardware and software systems in a comprehensive delivery with success metrics. Laise the concept and process across the enterprise. Compliant process definition and financial management with commercial model.
Technologies: 5G, RAN, SAP, Cloud, Enterprise Architect, Autonomous Robots, ITIL, CoBIT, TBM, BSI, ISO 27001
Peter P.
Last position:
Consultant Strategy & Digital at Polynova AG
- Designed the growth and digital strategy for an EU distributor
- Established a differentiation strategy focusing on horizontal portfolio expansion, ESG and SG&A cost reduction using new digital sales and service channels
- Offered same-day logistic delivery for key customers, increasing customer satisfaction by 25%
Gwang Jin K.
Last position:
Data Scientist / Applied AI, Automation & Data Systems Researcher at Independent
- Built and explored applied GenAI, RAG, GraphRAG, local LLM, agentic AI and document-intelligence prototypes for structured analysis, evidence extraction, semantic search, technical reasoning and decision-useful reporting
- Developed private local-LLM workflows and AI system patterns focused on privacy, reproducibility, reviewability, low-cost inference and practical user control
- Built reproducible Python/R workflows for data analysis, automation, API-driven tooling, validation logic, technical documentation and AI-assisted software development
- Designed workflows around explicit assumptions, traceable inputs, reviewable outputs and failure-mode awareness rather than black-box “looks good” demonstrations
- Supported RAHN AG in a chemical/regulatory environment with data extraction and processing around WERCS, a regulatory application for chemical product and compliance data
- Explored complex application/database schemas and wrote nested SQL queries to extract information for mixture calculations, component relationships, regulatory rules and reporting logic
- Continued hands-on development in Git/GitHub/GitLab/Bitbucket, Docker/Linux deployment patterns, REST/API workflows, error handling, technical writing and fast AI-assisted prototyping
- Built technical writing and documentation workflows that turn complex systems into clear runbooks, checklists, decision notes and user-facing explanations
Daniela H.
Last position:
Data-Based Transformation & Strategic Business Capability Mapping at CSS Versicherung
- Architected and implemented a Data Value Framework as a decision-making basis for strategic prioritization and determining data-driven value contributions along the corporate value chain, connecting data value with business objectives.
- Designed standardized use cases to assess the maturity levels for quantifying business value and data value.
- Integrated the framework within SAFe structures in Lean Portfolio Management and ARTs to guide strategic investment decisions.
- Developed metrics and evaluation procedures for prioritizing business areas based on quantitative data.
- Redesigned data governance, including the introduction of the data owner role with clearly defined responsibilities and differentiation from the data steward role.
- Derived MVP priorities using gap analyses across key areas and value stream analysis.
Ursula M.
Last position:
Business Mentor at RoleModel Rebels
- Mentor female students and professionals in advancing their careers, particularly as aspiring tech entrepreneurs.
Georgios S.
Last position:
Senior Software Engineer at UBS Bank
- Implementations of a code refactoring framework able to refactor thousands of repositories leveraging Generative AI
- Use Python (Django, Flask, FastAPI), Java and Typescript in Azure Cloud (Data Lake, VMs, AI) and GitLab infrastructure
- Mentoring and pair programming
- Obtained Azure AI-900 and AI-102 certifications
Discover over 15,000 top freelancers
Statistics of experts using Generative AI
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
2.4 years
Positions per freelancer
10
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Professional Services
Certification focus areas
Information Technology, Project Management, Research and Development
Bachelor's degree or higher
95%
Master's degree or higher
84%
Doctorate
21%
Certifications per freelancer
4
Most common languages
German, English, French
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 Switzerland 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 Switzerland using Generative AI
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.
Generative AI 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 (90%)
- Banking and Finance (71%)
- Professional Services (52%)
- Education (43%)
- Insurance (43%)
- Healthcare (38%)
- Manufacturing (33%)
- Government and Administration (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Generative AI does
Generative AI creates new content from learned patterns. It can produce text, images, audio, video and software code, then adapt outputs to a company’s data and workflows. Large language models such as GPT, Claude and Gemini are common foundations for conversational and document-focused applications.
Products it enables
Companies use Generative AI to improve how people search, write, analyse and interact with information.
- Customer support assistants grounded in approved knowledge
- Internal search and question-answering tools
- Document extraction, summarisation and drafting workflows
- Personalised content and recommendation experiences
- Code assistance and software delivery tools
Ecosystem and tooling
Strong work spans model selection, prompt design, embeddings, vector databases and retrieval-augmented generation. Professionals may work with APIs from OpenAI, Anthropic or Google, open-source models from Hugging Face, and orchestration tools such as LangChain or LlamaIndex. Python, TypeScript, cloud services, data pipelines and evaluation frameworks complete the delivery stack.
When expertise matters
Freelance expertise helps when a proof of concept must become a dependable product, or when an existing application needs safe model integration. In Switzerland, projects may also need clear multilingual behaviour, careful handling of business data and collaboration across remote and on-site teams.
- The prototype gives inconsistent or unverifiable answers
- Costs, latency or model selection need tighter control
- Private documents must be connected without exposing them
- Teams need evaluation, monitoring and fallback strategies
What strong professionals deliver
Experienced specialists define useful boundaries before choosing a model. They design prompts and retrieval flows, establish representative test sets, measure groundedness and relevance, and protect confidential data. They also plan human review, access controls, logging and graceful failure instead of treating fluent output as proof of accuracy.
Choosing the right specialist
Look for evidence of shipped Generative AI systems, not only demonstrations of chat interfaces. Ask how the professional handled hallucinations, changing model behaviour, prompt injection, data retention and user feedback. The best fit combines model knowledge with product thinking, backend integration, security awareness and the communication needed to explain trade-offs clearly.
Frequently asked questions
Not sure where to start with Generative AI? These answers cover the essentials.
Generative AI is used to create and transform text, images, audio, video and code. Common applications include support assistants, document analysis, internal search, content production and software delivery workflows.
Generative AI handles flexible, language-rich tasks where inputs and outputs vary, while traditional automation is usually more predictable and rule-based. Many effective systems combine both: a model interprets a request, and deterministic services validate or execute the result.
A strong Generative AI professional often combines Python or TypeScript with API integration, data engineering, cloud infrastructure and security. Experience with embeddings, vector databases, prompt design, evaluation and retrieval-augmented generation is especially useful.
The right level depends on the risk and scope of the work. A simple prototype may need focused model and integration skills, while a production system requires experience with evaluation, monitoring, privacy, access control and operational resilience.
Yes, Generative AI work can usually be delivered remotely when data access, collaboration routines and deployment responsibilities are clearly defined. On-site sessions can still help with discovery, stakeholder alignment and workshops, particularly for regulated or multilingual environments in Switzerland.
Ask the Generative AI specialist to explain how they test factuality, relevance, safety, latency and cost using realistic examples. Review production decisions, failure handling and data protection practices rather than judging a project only by how fluent its demo sounds.
Generative AI can use approved documents, databases and APIs through retrieval or tool connections instead of relying only on model training. The data should be current, well-structured and permission-aware, with controls that prevent users from receiving information they are not allowed to access.
A Generative AI feature should address hallucinations, prompt injection, confidential-data exposure, copyright questions, biased outputs and changing model behaviour. A sound design includes evaluation, human escalation, logging, access controls and a fallback path when the model is uncertain.
The average hourly rate of freelancers in Switzerland who have used Generative AI in their recent projects is 117 €, which corresponds to a daily rate of about 937 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Generative AI in their recent projects, 95% hold at least a Bachelor's degree, 84% hold at least a Master's degree, and 21% hold a doctorate.
On average, freelancers in Switzerland who have used Generative AI 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 Switzerland who have used Generative AI in their recent projects are German (100%), English (100%), and French (48%).
The most common industries among freelancers in Switzerland who have used Generative AI in their recent projects are Information Technology (90%), Banking and Finance (71%), and Professional Services (52%).
The most common business areas among freelancers in Switzerland who have used Generative AI in their recent projects are Information Technology (95%), Product Development (90%), and Project Management (57%).
Main locations of FRATCH Experts, who have recently used Generative AI
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.
Zurich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
