Large Language Model Experts in Switzerland
matched in minutes from over 15,000 CVsHire experts who design LLM applications, build retrieval-augmented generation systems and connect GPT models to business data and workflows. Find vetted, available freelancers in Switzerland through fast, precise AI matching.
Meet FRATCH Experts in Switzerland, who have recently used Large Language Model
Matthias S.
Last position:
Lecturer in Software Management at Graubünden 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
Vincent V.
Last position:
IT Business Partner & Enterprise Architect at Sulzer
- Established the Enterprise Architecture function from the ground up for Sulzer Group (~13,500 employees, CHF 3.6B revenue)
- Defined the Technical Governance framework, Target Operating Model, and IT PMO foundation now governing architecture decisions and portfolio demand across all divisions.
- Deployed SAP LeanIX as the authoritative application portfolio system of record - catalogued 500 applications group-wide (140 for Chemtech), onboarded business and IT stakeholders, and initiated integration with ServiceNow to embed architecture data into operational workflows.
- Led the divisional & group wide Application Rationalization initiative
- Decommissioned 15% of the 140 applications Chemtech portfolio, delivering CHF 627k in run-rate savings over two years and materially reducing licensing and support exposure.
- Defined and executed the divisional AI Roadmap in partnership with Sales, Legal, and R&D leadership
- Delivered 4 AI solutions into production (including Sales process harmonization and LLM-based IP conflict detection) from a portfolio of 7 prioritized initiatives.
- Built and owned the 3-year IT Strategic Roadmap for Chemtech
- Aligned cloud and technology architecture with divisional business priorities and a CHF 1.5M annual investment envelope.
- Delivered CHF 500k in cost avoidance by challenging and discontinuing funded but low-value initiatives, demonstrated governance discipline and executive influence, with zero implementation spend.
Mike B.
Last position:
Freelance UX-Researcher, Designer at Bodensee Schiffsbetriebe; Labhard-Medien
- UX research, UX concept development, and UX design for an AI dialogue system with information on events, locations, public transport timetables, and special trips. Observations, remote user tests, session recordings, analytics evaluations, RapidUserTests, prototyping, etc., using Figma/Figma Make, Claude Design, and OpenAI Codex (Design)
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
Mohamad K.
Last position:
Senior Backend Developer at Standing on Giants
- Led architecture and end-to-end engineering delivery for community-driven SaaS platforms serving 2M+ monthly active users.
- Architected and led the migration of a monolithic Python/FastAPI and PostgreSQL database and LangChain with codebase to an event-driven microservices architecture on AWS EKS, sustaining 10x traffic growth from ~150 RPS to 1,500+ RPS with zero re-architecture cycles.
- Defined and enforced engineering standards across services including API contracts, observability baselines, and deployment topology, reducing production incidents by 55% and MTTR from 2 hours to under 25 minutes within 9 months.
- Redesigned the caching and query layer using multi-tier Redis caching and database indexing/partitioning, cutting p95 API latency from 850ms to 180ms (78% reduction) and database CPU load by 45%.
- Built CI/CD platform on GitHub Actions, Terraform, and Kubernetes (EKS) with blue-green and canary rollouts, increasing deployment frequency from ~2/month to 8-12/day and reducing lead time from 10 days to under 6 hours.
- Implemented contract testing, automated load testing, and observability SLOs using Prometheus, Grafana, and OpenTelemetry, raising platform availability from 99.5% to 99.95% (10x reduction in error budget burn).
- Led and grew a cross-functional team of 8 engineers across backend, frontend, and DevOps, scaling headcount from 4 to 8 with 85% retention; owned hiring, onboarding, performance reviews, and career development.
- Partnered with Product, Design, and Client Success leadership as primary technical decision-maker; translated business goals into technical roadmaps and drove build-vs-buy decisions on authentication, search, and AI tooling.
- Introduced AI-assisted development workflows including automated code review and a RAG-based internal knowledge assistant using Graph (GraphRAG, Neo4J), increasing sprint throughput by 30% across two quarters.
- Owned incident command and production support rotation; established runbooks, postmortem culture, and on-call SLOs, reducing weekend paging incidents by 70%.
- Developed and optimized Algorithms using python libraries like Numpy and Pandas.
Robin O.
Last position:
Co-Founder & AI Solutions Architect at airdys
- Product strategy, architecture, and technical co-direction
- AI workshops, client onboarding and go-to-market activities
- Design and implementation of AI architectures (LLMs, RAG, MCP, agents, voice, automation)
- Hands-on development of prototypes and production-ready AI integrations
- Consulting clients on AI adoption, workflows, and integration into existing infrastructure
- Collaboration with co-founders on strategic direction
- Collaboration in sales and customer acquisition
Tools and Technologies: OpenAI, Anthropic, Azure, Vercel AI SDK, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), FastAgent, VAPI, n8n, make.com, LibreChat, PostgreSQL, OpenAPI, Next.js, Vercel, Docker
Ralf R.
Last position:
Security Architect at Federal Employment Agency
Responsibility for the design, migration, and integration of a security- and audit-critical HashiCorp Vault platform in the trust center of a nationwide authority with system-critical importance.
Analysis and realignment of the existing HashiCorp Vault landscape, including production and planned use cases
Design, proof-of-concept, migration, and integration of HashiCorp Vault Enterprise, taking into account the authority's PKI and operational processes
Design and implementation of an automated certificate and secrets management system for 300 Kubernetes clusters and several thousand certificates in the trust center
Securing the Vault platform using hardware security modules (HSM)
The solution enables a highly available, audit-compliant, and automated operation of certificate and secrets use cases in a highly regulated environment.
Technologies used: HashiCorp Vault Enterprise, Terraform, Ansible, OpenSSL, PKI, HSM
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.
Daniel S.
Last position:
Senior Manager at devpoint GmbH
- Design and co-implementation of an insolvency management platform in Germany for a client (based on an AI development tool)
- Concept, requirements engineering, and implementation support for a Dubai-based company to integrate processes into a CRM
- Business analysis and requirements engineering at Swisscom for integrations
- Integration of a new knowledge management system into the business processes at Swisscom AG – REST API definition
- Project manager, consultant, and sparring partner for the realignment/process digitalization at GIB Solutions AG
- Process designer and prototype for an AI-based real estate marketing system in Dubai
- Interim head of the ICT department at a telecom company, reorganizing and optimizing processes with a team of 5 at GIB Solutions AG
- Agile requirements engineer / external PO for a web-based solution for the German company DEHN AG
- Project management and consulting for the existing marketing and campaign planning solution at Swisscom AG
- Building the ALoHA nearshore offering at devpoint
Stefan H.
Last position:
Fullstack Development, Product Owner & Tech Lead at Trex AG
- Business analysis, architecture, and implementation of a telemedicine platform for pet owners.
- Leading the development team as Product Owner and Tech Lead.
- Introducing agile processes, setting up development guidelines and system documentation.
- Planning and implementing features like video calls, live chat, and marketing automation.
- Implementing AI-based features such as automated tagging of information (missing pet reports, marketplace entries, etc.), preparation of social media content, and processing of conversation transcripts.
- Skills: Angular, NGXS, Tailwind, Java, Spring Boot, Kubernetes, Docker, CI/CD, MySQL, LLMs, RAG, MCP, Redis, OpenSearch.
- Industry: Veterinary medicine.
Fabian K.
Last position:
Lecturer at HWZ University of Applied Sciences
- Co-teach in CAS AI Management and CAS AI Innovation programs for future AI managers
- Cover topics including data platforms, AI architecture, technology adoption foundations, and factors influencing enterprise AI initiative success
Matthias I.
Last position:
Fractional CTO (Principal Engineer / Technical Architect)
- Designed large-scale systems and APIs serving thousands of concurrent users.
- Refactored a 650k-LOC monolith and led full AWS migration for stable performance.
- Introduced SLO-based observability, improving reliability and recovery flow.
- Optimised cloud and databases, achieving significant cost and latency reduction.
- Delivered LLM, RAG, and document-automation pipelines adopted in production.
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
Alejandro A.
Last position:
AI Researcher & Engineer at Tufa Labs
- Deployed and optimized the inference stack on a multi-node DGX B200 cluster across vLLM and SGLang (serving, throughput and latency tuning).
- Built, with a small team, an internal Python library for LM pretraining covering the full training loop: distributed training with PyTorch FSDP, data pipelines, checkpointing, config and hyperparameter management, and experiment tracking.
- Built and evaluated agent scaffolds on interactive game benchmarks similar to ARC-AGI-3, with metrics for how models plan, explore and adapt across multi-step episodes; classified model errors and fed the findings back into scaffold and evaluation design.
- Researched looped transformer architectures.
Karl E.
Last position:
incl. CI/CD, automation at AALS Software AG
- Designed and delivered a practical real-time course on Flink and Hadoop with MapReduce, HDFS, Spark, Flink, Hive, HBase, MongoDB, Cassandra, and Kafka
- Gained extensive DevOps and CI/CD experience
- Created ETL/ELT pipelines with Apache tools and Pentaho
- Led projects in municipal software, financial services, and big data with Kafka
- Developed AI/NLP models and chatbots with RASA, Chatter, and Dialogflow
- Built and managed a TypeDB knowledge database
- Worked with OpenStack, Kubernetes, and Podman
Discover over 15,000 top freelancers
Statistics of experts using Large Language Model
Aggregated from the professional profiles of matched freelancers.
Experience
21 years
Position duration
2 years
Positions per freelancer
12
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
100%
Master's degree or higher
73%
Doctorate
13%
Certifications per freelancer
4
Most common languages
English, German, French
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 Switzerland 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 Switzerland 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 (94%)
- Banking and Finance (75%)
- Professional Services (56%)
- Education (50%)
- Automotive (31%)
- Energy (31%)
- Healthcare (31%)
- Insurance (31%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What LLMs do
A Large Language Model, commonly called an LLM, learns patterns from extensive text and generates or transforms language in response to prompts. Companies use LLMs to build conversational assistants, document tools, search interfaces, content workflows and software features that understand natural language. GPT models are widely used examples within this technology family.
Typical applications
LLM projects turn unstructured information into useful actions and answers.
- Customer and employee support assistants
- Retrieval-augmented generation over private documents
- Summarisation, classification and information extraction
- Text generation, translation and writing support
- Natural-language interfaces for business systems
Ecosystem and tooling
Strong work with LLMs combines model selection, prompt design and production software. Professionals may work with hosted APIs from OpenAI, Anthropic or Google, open-weight models such as Llama, and orchestration tools such as LangChain or LlamaIndex. Vector databases, embeddings, evaluation suites, Python services and cloud infrastructure are common parts of the stack.
When companies need specialists
Freelance expertise helps when a team must validate an LLM use case, connect a model to internal knowledge or move a prototype into reliable operation. It is especially valuable when data is sensitive, responses need traceability, or model costs and latency must be controlled. In Switzerland, remote collaboration can work well, while regulated industries may also require on-site workshops and clear language support across German, French, Italian or English.
Delivery and integration
LLM professionals define prompts, data flows and safeguards before implementation. They connect models to APIs, identity systems, CRM software and internal databases, then add retrieval, tool calling, structured outputs and human review where needed. A complete delivery includes deployment, monitoring, documentation and a plan for handling outdated, incomplete or unsafe answers.
What distinguishes strong experts
The best specialists treat language output as a system that must be tested, not as a feature that can be accepted on appearance alone. They create representative evaluation sets, measure factuality and relevance, protect confidential data and explain trade-offs between hosted and self-managed models. They also know when a conventional search, rules engine or smaller model is more suitable than an LLM.
Frequently asked questions
Questions about Large Language Model? Start with the answers below.
A Large Language Model can support conversations, summarise documents, extract structured information and answer questions over company knowledge. It can also call business tools, draft content and provide a natural-language interface to existing software.
An LLM can interpret varied language and generate flexible responses rather than relying only on fixed rules and decision trees. A reliable business chatbot still needs defined data access, guardrails, testing and escalation paths around the model.
A GPT model may offer strong general performance and convenient hosted access, while open-weight models can provide more control over deployment and data handling. The right choice depends on privacy, languages, context size, latency, integration effort and the quality required for the use case.
An LLM specialist should usually understand APIs, Python or another service language, embeddings, vector search and cloud deployment. Experience with data security, prompt evaluation, retrieval-augmented generation and product integration is equally important.
A Large Language Model proof of concept may need focused expertise in prompt design and API integration, while a production system requires broader skills. Look for experience with evaluation, observability, access control, cost management and failure handling at the intended level of business risk.
A Large Language Model project is often suitable for remote collaboration when repositories, data access and communication routines are well organised. Swiss companies may still prefer on-site discovery sessions, and language expectations should be agreed early when users work in German, French, Italian or English.
A strong LLM solution has a clear evaluation method based on representative user questions and expected outcomes. Ask how the specialist handles hallucinations, prompt injection, sensitive data, model changes, human review and measurable acceptance criteria.
A Large Language Model is not always suitable for deterministic calculations, strict rule enforcement or simple searches over well-structured data. A conventional application, database query or rules engine may be safer, cheaper and easier to validate for those tasks.
The average hourly rate of freelancers in Switzerland who have used Large Language Model in their recent projects is 118 €, which corresponds to a daily rate of about 943 € based on an 8-hour working day.
Of the freelancers in Switzerland who have used Large Language Model in their recent projects, 100% hold at least a Bachelor's degree, 73% hold at least a Master's degree, and 13% hold a doctorate.
On average, freelancers in Switzerland who have used Large Language Model in their recent projects have 21 years of professional experience, with a single engagement typically lasting around 2 years.
The most common languages among freelancers in Switzerland who have used Large Language Model in their recent projects are English (100%), German (88%), and French (50%).
The most common industries among freelancers in Switzerland who have used Large Language Model in their recent projects are Information Technology (94%), Banking and Finance (75%), and Professional Services (56%).
The most common business areas among freelancers in Switzerland who have used Large Language Model in their recent projects are Information Technology (100%), Product Development (88%), and Project Management (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.
Zurich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
