Generative AI Experts in Berlin
matched in minutes by AIHire experts who design AI assistants, retrieval-augmented generation systems and content workflows with models such as GPT, Claude and Gemini. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts in Berlin, who have recently used Generative AI
William N.
Last position:
Power BI Solutions Architect/Engineer & AI Consultant at AVERDUNG GmbH
- Redesign of the company's BI infrastructure: replacement of a fragmented landscape of manually maintained Excel solutions and CSV imports with a centralized Power BI environment featuring a unified data model as the company-wide single source of truth
- Consolidation of previously isolated reporting logic into a central semantic model – eliminating redundant files, manual data transfers, and inconsistent metrics between departments
- Forecasting & planning: Design and implementation of company-wide liquidity planning in Power BI – from business logic to a fully automated, data-source-driven planning model replacing the previous manual Excel process; enables rolling forecasts and continuously up-to-date cash flow transparency for management
- Optimization of existing Power BI dashboards in terms of performance, structure, and analytical value using an AI-native approach
- Analysis and improvement of the data model, including data quality analyses, data cleansing, and consistent modeling using star schema, DAX, and Power Query
- Incident & anomaly analysis: Identification, investigation, and explanation of data anomalies, including root-cause analysis and concrete recommendations for action
- AI solution architecture: Connecting Business Central and Power BI to LangDock via MCP (Model Context Protocol) for AI-supported data usage
- Creation of a historical data layer as a basis for trend and time-series analyses
- AI-supported automation: Design and development of AI skills, agents, loops, and processes for the automated analysis and interpretation of reports
- Automated reporting workflow: Setup of scheduled, automated email distribution of AI-generated analyses and recommendations to stakeholders
- Gathering and documentation of business requirements and coordination with business departments and IT as part of requirements engineering / product owner activities
- Breaking down overall requirements into clearly defined work packages and tasks
- Definition, prioritization, and management of milestones throughout the entire project lifecycle
Tools: POWER BI, M365, Copilot Studio, MIRO, Microsoft Business Central, Microsoft Fabric, Claude AI, ChatGPT, LangDock, MS VS Code
Bidya B.
Last position:
Product Manager – Payments & Platform at Pipedrive
CRM and revenue platform managing billing and subscription workflows.
- Scaled payments infrastructure across data products, direct debit expansion and automated abuse prevention, generating $416K in annualized operational savings ($8K/week) by eliminating redundant gateway calls.
- Owned backlog and sprint execution for autonomous checkout abuse detection pipelines, designing real-time risk guardrails and velocity heuristics that blocked card testing attacks.
- Architected enterprise billing migrator user stories and data reconciliation mechanisms, achieving zero-downtime subscription state transitions and cutting $60K in infrastructure overhead.
- Expanded European direct debit (SEPA) payment capabilities, managing cross-squad API dependencies and automated webhook error-handling to eliminate checkout friction.
Hubertus S.
Last position:
Senior Product Manager AI
Workflow-automation SaaS for operations teams (Berlin, 120 people); full-time freelance engagement reporting to the CEO: an initial 12-month interim mandate, extended twice through the AI build-out; owned product for one squad and coached the other product managers on process.
- Led generative AI (LLM) integration into the core product: from LLM-powered steps to natural-language workflow authoring and step-level automation suggestions, plus AI-managed dynamic workflows, shipped behind eval gates with human-in-the-loop fallbacks: AI-drafted workflows grew to 31% of all new workflows, and median time-to-first-workflow fell from 3 days to 4 hours.
- Packaged the AI capabilities as a usage-based add-on priced on executed automation steps, working with sales and marketing on positioning: ~€800K added ARR in the first year, and adopting accounts churned 1.8 pp less.
- Owned the roadmap end to end: replaced feature-request-driven quarterly planning with an outcome-based rolling roadmap built on quarterly bets and explicit kill criteria, presented monthly to the executive team and quarterly to the board.
- Rebuilt the product-management operating system: weekly customer-discovery cadence incl. workshop facilitation, RFC/decision-doc reviews and a single quarterly metrics narrative; coached four product managers, one promoted to senior during the engagement.
- Closed the engagement as scoped: hired and onboarded the permanent VP Product, handed over the process playbook and roadmap, and exited on schedule in June 2026.
Myrto P.
Last position:
UX Lead, Strategist for Property Management Systems at Destination Solutions
- Leading UX for a Property Management System, an all-in-one solution for vacation rental agencies and tourism regions, covering marketing and rental of holiday apartments and houses
- UX audits, conception, and implementation of UX strategy with a focus on regulatory, security, and user-centered requirements
- Advising C-level stakeholders on UX strategy and design best practices
- Planning and conducting research with agencies and property owners
- Design system strategy and definition of UX architecture
Pradeep S.
Last position:
Tech Product Lead – AI, Data & Platform Products at Elli GmbH- A brand of Volkswagen
- Own the 12–18 month roadmap and key outcomes for Elli's enterprise customer platform, covering onboarding, pricing, billing, analytics and broader platform modernization; redesigned the Fleet onboarding funnel to double conversion, supporting a projected €20.7M revenue uplift by 2028.
- Lead the broader Energy Intelligence product and directly own its AI/ML, asset and portfolio-optimization capabilities, including MLOps and safe strategy deployment, strategy lifecycle management and backtesting; delegated data and V2G integration roadmap ownership to a new PO as the platform scope expanded.
- Built a Human-in-the-loop GenAI/RAG support workflow, increasing L1 resolution by 24%, routing accuracy to 91%, and reducing L2 workload by 30%.
- Introduced standardized data contracts and a self-service Python toolkit for traders and Data Scientists, increasing platform adoption by 15% and reducing support effort by 50%.
- Built and scaled a real-time orchestration product from 32 to 3,000+ endpoints across four markets, growing recurring revenue from €1.4k to €56.3k MRR.
- Developed product and AI capability across the organization, training 20 PMs on RAG, agents and prototyping; mentoring a junior PM and coaching an Enterprise Platform Tech Lead toward Product Management ownership.
Rashi J.
Last position:
Design Consultant at Valutics Inc.
- Designing UX for a B2B AI SaaS platform covering the full software development lifecycle, including an orchestration transparency panel showing users which AI model is active at each stage, reducing AI opacity and building user trust in multi-model workflows.
Nikolai G.
Last position:
Clinical Data Manager at Dr. Falk Pharma
- Used OpenCode and AI-assisted software engineering to design, implement, refactor, test, and document an end-to-end RAW/SDTM/ADaM pipeline in R for Dr. Falk Pharma (07/2026), including metadata-driven transformations, automated validation rules and QC, traceability, and reproducible clinical outputs.
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Saman S.
Last position:
AI Product Builder at Instalemon.com
- Architected and built an agentic creative automation platform on Mastra, with a custom RAG pipeline, custom hooks, tools and skills, Chroma for vector storage, and a MongoDB/Express backend.
- Built the agent orchestration layer powering Pixomi's multi-agent workspace, including 72 custom marketing skills, tools and hooks, and a custom context-management pipeline.
- Designed and implemented evals and observability through Mastra studio.
- Onboarded 10 pilot SMB customers producing 10x publish-ready creative output per campaign versus manual production in 3 months.
- Ran customer discovery and pilot feedback loops to shape the roadmap for an AI-native, workflow-based creation platform.
Mukund B.
Last position:
Voice AI Chatbot - Real-Time Audio Assistant
- ▶ Built real-time voice assistant (STT → LLM → TTS pipeline) benchmarking and evaluating multiple STT providers including faster-whisper and Azure Speech. achieved sub-3s latency, Groq API (Llama 3) with multi-turn memory - directly handling edge cases in dictation, names and passcode recognition.
Elisabeth H.
Last position:
Interim Talent Acquisition at 1000 Satellites
1000 Satellites (Coworking Space, Scale-up, 50–250 employees)
Support for a scale-up with up to 30 open positions, from defining job profiles and preparing offers through to negotiations
Stefan S.
Last position:
Digital & AI Transformation, Agile Culture & Business Management Consultant & Project Manager at Freelance
- Freelance work as a consultant (workshops and coaching for small to midsize companies in the areas of lean startup methodology, digital & AI transformation strategy, agile culture, design thinking)
- AI training & certification
- Project Management
Aruldass A.
Last position:
Web Module Lead at Mphasis Limited
- Led the end-to-end delivery of enterprise full-stack web applications by driving requirement analysis, solution design, frontend and backend development, database design, API integration, code reviews, team coordination, Agile execution, CI/CD deployments, production support, performance optimization, security implementation, and stakeholder collaboration to deliver scalable, high-quality software solutions.
Julian L.
Last position:
Director Group B2B at Allegro
Responsible for the B2B business of Poland's largest e-commerce platform, including full P&L and product direction.
- Full P&L ownership for the B2B Group, responsible for 7bn PLN (~€1.6bn) in annual GMV
- Initiated and lead the business and product group transformation and strategy change to focus on SME customers, leading to a 100% increase in GMV growth (from 12% to 24% YoY)
- Drove AI-based process automation to 48% of B2B Group processes
Katharina V.
Last position:
Business Transformation & Organizational Effectiveness at Independent
Supporting organizations and leadership teams in business transformation, organizational effectiveness and strategic initiatives.
FOCUS AREAS: Business Transformation | Organizational Effectiveness | Strategy & Operations | Executive Advisory & Partnership | AI & Technology Organizations
Discover over 15,000 top freelancers
Statistics of experts using Generative AI
Aggregated from the professional profiles of matched freelancers.
Experience
15 years (Germany: 16 years)
Position duration
2.4 years (Germany: 2.3 years)
Positions per freelancer
9 (Germany: 10)
Top business areas
Product Development, Information Technology, Project Management
Top industries
Information Technology, Professional Services, Retail
Certification focus areas
Information Technology, Product Development, Project Management
Bachelor's degree or higher
97% (Germany: 96%)
Master's degree or higher
70% (Germany: 75%)
Doctorate
5% (Germany: 15%)
Certifications per freelancer
2 (Germany: 3)
Most common languages
English, German, Spanish
Speak two or more languages
93% (Germany: 97%)
Based on our profile pool as of 9 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Berlin 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 Berlin 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 9 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 (93%)
- Professional Services (45%)
- Retail (44%)
- Healthcare (41%)
- Banking and Finance (37%)
- Media and Entertainment (36%)
- Automotive (32%)
- Education (32%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What it does
Generative AI creates new text, code, images, audio and structured data from learned patterns. Companies use it to power conversational assistants, document workflows, search experiences, creative tools and software features. Unlike rule-based automation, it can respond to varied natural-language inputs and produce useful drafts or decisions.
Where it fits
- Customer support assistants grounded in company knowledge
- Retrieval-augmented generation for private documents and search
- Content generation, summarisation and translation workflows
- Coding assistants, review tools and test generation
- Image, audio and video creation for product experiences
These systems appear in software products, internal operations, media, retail, finance, healthcare and industrial environments. Strong implementations connect model output to business data, permissions and human review rather than treating a model response as automatically reliable.
Ecosystem and tooling
Professionals work with foundation models from OpenAI, Anthropic, Google and open-source communities. Common components include GPT, Claude, Gemini, Llama, embedding models, vector databases, prompt templates, evaluation suites and orchestration frameworks such as LangChain or LlamaIndex. Production work also involves APIs, Python or TypeScript, cloud services, data pipelines, observability and secure deployment.
When to bring expertise
- A prototype needs to become a dependable product feature
- Model selection, prompting or fine-tuning is producing inconsistent results
- Company documents must be searchable without exposing sensitive data
- Usage, latency and infrastructure need practical control
- Teams need evaluations, guardrails and monitoring before launch
Freelance specialists are useful when internal teams need focused delivery without building a permanent AI function. In Berlin, collaboration may combine remote delivery with on-site workshops, depending on security, product and stakeholder needs.
What strong specialists deliver
Good work starts with a clear use case, suitable data and measurable acceptance criteria. Strong professionals design retrieval and tool-use flows, test failure modes, protect personal and confidential information, and make it clear when a human must review an output. They document model choices and create evaluation sets that reflect real user questions.
Skills beside models
Generative AI projects often require product discovery, data engineering, backend integration, cloud operations, UX writing and security review. Specialists should understand token limits, embeddings, context design, structured outputs, latency and model costs without reducing the project to prompt writing. They also communicate uncertainty clearly and can work with German- and English-speaking teams in Berlin.
Frequently asked questions
Not sure where to start with Generative AI? These answers cover the essentials.
Generative AI is used to create text, code, images, audio and structured responses from natural-language instructions or application data. Companies apply it to assistants, document search, content operations, software tooling, research support and personalised product features.
Generative AI can interpret flexible language and produce new responses, while traditional automation follows defined rules and search primarily retrieves existing information. It is useful when inputs vary, but it needs grounding, validation and guardrails to reduce inaccurate or unsuitable output.
A strong Generative AI specialist may also work with Python or TypeScript, APIs, cloud infrastructure, data pipelines, vector databases and evaluation tooling. Security, UX, product discovery and backend integration are equally important when the model becomes part of a real application.
The right level depends on the project rather than a fixed number of years. A simple proof of concept may need focused model and API knowledge, while a production system requires experience with data access, evaluation, monitoring, privacy, failure handling and operational ownership.
Generative AI projects can often be delivered remotely through shared repositories, cloud environments and structured workshops. On-site collaboration in Berlin can still help with sensitive data, stakeholder alignment and discovery, while language expectations should be agreed before work begins.
Start with the user problem, source data, permitted actions and what counts as a satisfactory result. A Generative AI specialist can then assess model options, retrieval needs, integration boundaries, privacy controls and a sensible path from prototype to production.
Ask for representative evaluations rather than relying on an impressive demo. Quality in Generative AI includes factual grounding, consistent task performance, safe handling of sensitive data, clear fallback behaviour, useful monitoring and a transparent explanation of known limitations.
A Generative AI freelancer should clarify the model provider, data permissions, deployment environment, evaluation process and access to product stakeholders. In Berlin-based work, it also helps to confirm remote or on-site expectations and whether communication must support German, English or both.
The average hourly rate of freelancers in Berlin, Germany who have used Generative AI in their recent projects is 97 €, which corresponds to a daily rate of about 776 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Generative AI in their recent projects, 97% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 5% hold a doctorate.
On average, freelancers in Berlin, Germany who have used Generative AI in their recent projects have 15 years of professional experience, with a single engagement typically lasting around 2.4 years.
The most common languages among freelancers in Berlin, Germany who have used Generative AI in their recent projects are English (97%), German (93%), and Spanish (16%).
The most common industries among freelancers in Berlin, Germany who have used Generative AI in their recent projects are Information Technology (93%), Professional Services (45%), and Retail (44%).
The most common business areas among freelancers in Berlin, Germany who have used Generative AI in their recent projects are Product Development (88%), Information Technology (85%), and Project Management (52%).
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.
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Dusseldorf 
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