
Google Gemini Experts in Vienna
matched in minutes by AIHire experts who design Gemini-powered assistants, connect models to business data and build reliable multimodal workflows. FRATCH matches you quickly with vetted, available freelancers whose skills fit your project.
Meet FRATCH Experts in Vienna, who have recently used Google Gemini
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.
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
Agnes N.
Last position:
Senior Technical Project Manager at LastPass
- Acting as the sole program owner for BizMax and SaaS Monitoring products, integrating enterprise business insights with platform reliability and health monitoring to drive revenue growth and operational confidence.
- Own delivery of complex B2B technical initiatives at LastPass, driving implementation of innovative security and platform features across the broader zero-knowledge ecosystem.
- Work with backend, frontend and DevOps teams; manage stakeholders from Product, Marketing, Engineering, Architecture, Security, Platform, UX, and Quality to define scope, priorities, success metrics, and delivery plans while driving technical decision processes.
- Lead program planning and execution across multiple workstreams, ensuring delivery on time, within scope, and aligned with business objectives; mentor cross-functional teams and act as the primary escalation point to remove blockers and maintain delivery momentum.
- Drive annual strategic planning and budgeting, working with senior leadership and directors to align priorities, secure funding, and optimize resource allocation; proactively identify, manage, and mitigate technical, delivery, and dependency risks throughout the full program lifecycle, escalating issues early to minimize impact.
- Lead internal dogfooding initiatives and external beta programs, collaborating directly with customers to validate functionality, usability, and performance.
- Support go-to-market activities by contributing to customer-facing content, including blogs, talks, and product communications; own go-live readiness, hypercare coordination, and program closure, ensuring lessons learned are captured and applied for continuous improvement.
- Successfully led a large-scale greenfield program, designing and implementing end-to-end delivery and governance processes from scratch to deliver SaaS Monitoring and BizMax features, generating a multimillion-dollar increase in ARR and becoming a major revenue stream for the company.
- Designed repeatable AI-assisted workflows that improve planning accuracy and reporting efficiency.
- Founded and implemented standardized cross-team PMO processes and templates, including project overview, project brief, T-shirt sizing, risk register, ADR/RFC, release rollout plan, CAB, program closure, lessons learned, internal and external beta programs, and dogfooding, establishing a company-wide framework supporting delivery of the largest-scale programs.
- Mentored junior team members, new hires, and employees undergoing transformation initiatives, supporting skills development and adoption of modern delivery practices.
Marcel T.
Last position:
Founder, AI Strategy and Enablement at Engineering Peak Impact
- Design workshop curricula for software engineers and technical leads on AI-enabled engineering and on adopting AI tools effectively.
- Technical talk, 17th TestIstanbul Conference, October 2026: "What If We Tested the Tester?", on how AI amplifies the tester's judgement, blind spots included.
- Built and run the company website and online course platform (WordPress, PHP, JavaScript) with Claude Code and Cursor, plus a Playwright test suite that checks the live site's pages, links and sign-up flow.
- Built Write Check, a Chrome extension backed by a local Node.js service that scores any text box for clarity and AI-sounding phrasing, falling back across Gemini, Kimi, GPT and OpenRouter when a provider fails.
- Built a Python video pipeline that turns my online course into short narrated videos: script, text-to-speech, captions and rendering, with a review gate before each episode.
- Work under a written protocol for AI coding agents (CLAUDE.md): a definition of done written as checks before the work starts, tests that fail before they pass, and independent reviewer agents that check each claim of the coder agents against its source.
- Author of The Maintenance Trap (Level Up newsletter, May 2026), on developer productivity: why high-performing engineers get pulled into maintenance work and how to make the ROI case for fixing it.
Discover over 15,000 top freelancers
Statistics of experts using Google Gemini
Aggregated from the professional profiles of matched freelancers.
Experience
19 years

Position duration
2.3 years

Positions per freelancer
13

Top business areas
Information Technology, Product Development, Project Management

Top industries
Information Technology, Banking and Finance, Healthcare

Certification focus areas
Information Technology, Human Resources, Marketing
Bachelor's degree or higher
100%
Master's degree or higher
83%
Doctorate
17%

Certifications per freelancer
5

Most common languages
English, German, Spanish

Speak two or more languages
100%
Based on our profile pool as of 5 Nov 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 Google Gemini
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 5 Nov 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Google Gemini 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 (100%)
- Banking and Finance (67%)
- Healthcare (67%)
- Professional Services (67%)
- Retail (67%)
- Food and Beverage (50%)
- Manufacturing (50%)
- Media and Entertainment (50%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Google Gemini does
Google Gemini is Google’s family of generative AI models for working with text, images, audio, video and code. Companies use it to create conversational products, automate knowledge work, analyze mixed data and add natural-language interfaces to existing software. Gemini is available through Google AI Studio, the Gemini API and Google Cloud’s Vertex AI.
Products and use cases
Gemini supports both customer-facing experiences and internal workflows. It can summarize documents, extract structured information, generate content, answer questions over company knowledge and assist with software delivery.
- Build support assistants and research tools
- Process contracts, reports and other business documents
- Create multimodal search and analysis features
- Add code generation and review to engineering workflows
- Prototype and deploy generative AI applications
Ecosystem and tooling
Strong specialists work across Google’s AI ecosystem rather than treating the model as an isolated API. Common components include Vertex AI, Model Garden, Google AI Studio, Gemini API, BigQuery, Cloud Storage, Cloud Run and Google Kubernetes Engine. Production work also involves prompt design, structured output, function calling, retrieval-augmented generation and evaluation.
When companies need specialists
Freelance expertise is useful when a team must move from an experiment to a dependable product. Specialists can select the right Gemini model, connect private data safely, define evaluation methods and integrate the result with existing services.
- A prototype gives inconsistent or unverifiable answers
- Company data must be retrieved with clear access controls
- A workflow needs multimodal input or structured output
- Cloud deployment, monitoring or cost control is missing
What strong professionals deliver
Experienced Google Gemini professionals translate business goals into testable AI behaviour. They define prompts and schemas, protect sensitive data, handle errors and design fallback paths instead of relying on impressive demonstrations. They also compare model quality, latency and operating effort against the needs of the product.
For teams in Vienna, remote collaboration can work well when documentation, review routines and ownership are clear. On-site workshops may help during discovery, especially when product, legal and domain specialists need to agree on acceptable outputs.
Choosing the right fit
Look for evidence of shipped Gemini or generative AI work, not only familiarity with model terminology. Ask how the professional evaluates factuality, manages prompt and model changes, secures data and monitors production behaviour. Relevant adjacent skills include Python or TypeScript, API integration, cloud architecture, data engineering, identity management and responsible AI practices.
A good engagement starts with a defined use case, representative data and agreed quality criteria. The specialist should make limitations visible, explain trade-offs clearly and leave the team with maintainable prompts, tests, documentation and deployment processes.
Frequently asked questions
Not sure where to start with Google Gemini? These answers cover the essentials.
Google Gemini is used for conversational assistants, document analysis, multimodal search, content generation and software support. It can also connect business applications to model-powered workflows through the Gemini API or Vertex AI.
Google Gemini is often considered alongside OpenAI models and other foundation models. The right choice depends on multimodal requirements, response quality, integration with Google Cloud, data controls, evaluation results and the operating needs of the product.
A strong Google Gemini specialist usually combines prompt design with API integration, Python or TypeScript, cloud services and data engineering. Retrieval-augmented generation, function calling, evaluation, identity management and responsible AI are also valuable for production work.
A proof of concept may need a specialist who can work quickly with the Gemini API and representative data. A production system calls for broader Google Gemini experience, including testing, security, monitoring, failure handling and model-change management.
Yes. Google Gemini work is often suitable for remote collaboration when requirements, data access, review practices and ownership are documented. Vienna-based teams may still prefer on-site workshops for discovery, stakeholder alignment or sensitive domain discussions.
Ask a Google Gemini specialist to explain the evaluation set, success criteria, known failure modes and safeguards. Review whether the implementation produces traceable results, protects private data, handles uncertain answers and remains maintainable after prompts or models change.
Google Gemini supports multimodal work with inputs such as text, images, audio and video, depending on the selected model and service. Specialists can use those capabilities for document understanding, visual analysis, media workflows and richer assistants rather than text-only chat.
A Google Gemini freelancer should clarify the model access method, data boundaries, expected output format, evaluation process and deployment environment before starting. Familiarity with Vertex AI and Google Cloud helps when the work must move beyond a prototype into a governed production service.
The average hourly rate of freelancers in Vienna, Austria who have used Google Gemini in their recent projects is 129 €, which corresponds to a daily rate of about 1,030 € based on an 8-hour working day.
Of the freelancers in Vienna, Austria who have used Google Gemini in their recent projects, 100% hold at least a Bachelor's degree, 83% hold at least a Master's degree, and 17% hold a doctorate.
On average, freelancers in Vienna, Austria who have used Google Gemini in their recent projects have 19 years of professional experience, with a single engagement typically lasting around 2.3 years.
The most common languages among freelancers in Vienna, Austria who have used Google Gemini in their recent projects are English (100%), German (83%), and Spanish (67%).
The most common industries among freelancers in Vienna, Austria who have used Google Gemini in their recent projects are Information Technology (100%), Banking and Finance (67%), and Healthcare (67%).
The most common business areas among freelancers in Vienna, Austria who have used Google Gemini in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (100%).
Main locations of FRATCH Experts, who have recently used Google Gemini
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.
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