AI Solution Architects in Germany
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Meet FRATCH AI Solution Architects in Germany
Burhan Dinler
Last position:
Enterprise Architect & Solution Architect at DB Netz AG
With project PRIZMA, DB will modernize its infrastructure on the one hand, and develop a fail-safe IT landscape on the other hand, which can be restored quickly and securely in case of a disaster.
- Capture current architectures of existing systems as well as methodical consulting and development of target architectures
- Deepen and maintain the building plan / target IT landscape
- Implement technical architecture concepts & architecture descriptions
- Implement migration concepts for updating and further developing the platform and information systems
- Assess submitted improvement suggestions as part of the project
- Capability management: identify capability gaps, develop target visions, and support transformation planning within the enterprise architecture.
- Create a compatibility matrix of the components in use and compare dependencies of specific versions
- Create an IT concept for extending the platform with the following topics: hardware and software requirements, security, licensing, high availability, load balancing, backup & recovery, update strategy, monitoring integration, etc.
- Coordinate with business architects as well as technical architects from the cross-functional architecture area of the PRISMA program for the topics (backup, Active Directory, monitoring, Citrix, and business applications ...)
- Status meetings and alignment of project planning with the Release Train Engineer / Project Manager
- Advise the Release Train Engineer / Project Manager in identifying project risks
- Advise the System Architect Engineers in steering the implementation of the concept
- Implement the IT concept
- Document the infrastructure
Label: MS Project, LINUX, Windows, ORACLE, Java, REST, SharePoint, Microsoft Exchange, UML, Enterprise Architect, BPMN, AZURE, AWS, V-MODEL, Micro Service, VisualStudio, SAP S/4HANA, SCRUM(SAFE), ESB (TIBCO), Python, Innovator, LeanIX (TOGAF), Ansible, Ansible Tower, Ansible Automation, ROBOT, SpringBoot
Martin Hermann
Last position:
Lead Product Owner at Energy
- Team leadership: Prioritization and coordination of four cross-functional teams.
- Platform strategy: Development and implementation of strategies to optimize existing IT platforms.
- Stakeholder management: Active management of expectations and communication with internal and external stakeholders.
- Program and innovation management: Prioritization and coordination of cross-department projects as well as innovation initiatives.
- Product Owner consulting: Advising Product Owners with a focus on product development and continuous product improvement.
- Organizational development: Improving communication and decision-making structures across all organizational levels.
- Change management: Implementing best-practice change management methods to ensure continuous optimization and innovation.
- Quality assurance: Ensuring high quality standards in processes, services, and deliverables.
Daryoosh Dehestani
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
Daniel Arnan
Last position:
Sales Development Representative (SDR) at TenderFlow GmbH
- Acquires new B2B customers for an AI SaaS startup in the public tendering space and books product demos with IT decision-makers.
- Qualifies target customers based on a defined ideal customer profile, including discovery, needs analysis, and objection handling.
- Builds domain knowledge in public procurement (EVB-IT, German and EU tender portals) for technical discussions at eye level.
Artyom Narimanyan
Last position:
AI Automation Engineer & Solution Architect at Technology Research Project
Designed and developed an AI-powered automation platform using n8n to analyze social media niches, identify target audiences, and automate marketing strategy generation. The solution combined AI agents, workflow orchestration, and data analysis to automate research processes and generate data-driven insights.
- Designed and implemented complex automation workflows using n8n
- Developed AI-powered analysis agents for market and audience research
- Integrated multiple APIs and AI services into automated workflows
- Built automated market, competitor, and target audience analysis pipelines
- Leveraged Large Language Models (LLMs) for information summarization, classification, and prioritization
- Containerized and deployed the platform using Docker
Technologies: n8n, AI Agents, OpenAI APIs, Prompt Engineering, LLMs, Docker, Linux, REST APIs, Webhooks
Hoa Josef Nguyen
Last position:
AI Architect and Enabler at Inhouse / AI Business
Technologies: n8n, Notion, OpenAI API, Claude, MS AI Foundry, MS CoPilot Studio, MS CoPilot, LLM, Node.js, Vercel, LangGraph, PostgreSQL, pgEdge, pgvector, Docker, LangChain, Ollama, Open WebUI
- Continuous evaluation and prioritization of internal automation needs
- ~20 AI agents in active use: research, content pipelines, document processing
- 5 n8n workflows for automated data and process control
- Architecture built on the same principles as in customer projects: state management, event-driven orchestration, API integration
- Ongoing operation and further development
Hamdi Rajab
Last position:
Full-Stack AI Developer at Karray-Pflege GmbH
PFS-Matching-App
- Integrated an intelligent LLM chatbot using LangChain4j, enabling conversational AI, context-aware question answering, document summarization, and autonomous tool execution.
- Implemented Retrieval-Augmented Generation (RAG), prompt engineering, and AI agent workflows to connect large language models with enterprise data and backend services.
- Developed RESTful APIs and secure backend services to support AI-driven interactions and business processes
Uwe Schwarz
Last position:
Technical Program Lead IPv6 Migration at Deutsche Rentenversicherung (RP, BW)
- Technical program ownership for the IPv6 migration at DRV RP and DRV BW, with a focus on migration planning, execution structure, and cross-functional technical coordination.
- Designed and implemented an operational control model with dashboard, action board, KPI portfolio, risk register, and decision index to translate technical topics into structured delivery artifacts.
- Coordinated technical groundwork for architecture and rollout across IPv6 addressing, segmentation, dual-stack target design, test-lab planning, and cross-team dependencies.
- Supported security and compliance-related requirements in the context of BSI, NIS2, and critical infrastructure, translating them into traceable evidence, risks, and management reporting.
- Achievement: Established a reusable intake-to-governance workflow for systematically capturing technical actions, risks, open issues, and evidence requirements.
- Achievement: Created an operational baseline for technical program execution with measurable KPIs, clear ownership, and transparent decision support.
Ralph Behrens
Last position:
Senior Solution Architect Cloud, Data & AI at Sogeti Deutschland GmbH – Part of Capgemini
Evaluation, structuring, and handling of complex tenders for Sogeti as well as as part of larger Capgemini proposals. Focus on analyzing demanding customer requirements, deriving solid solution concepts, and translating technical, functional, and commercial aspects into convincing proposal storylines. In close alignment with delivery, sales, account, and bid teams, scalable and implementable Quality Engineering solutions were designed, evaluated, and prepared for customer decisions. This included selecting suitable role profiles and right-shore staffing options, assessing available skills and capacities, as well as the commercial preparation of reliable price and effort calculations.
A special focus was on bid management and handling service proposals (RfP/RfI analysis), solution design, presentation and management materials, as well as the functional and technical evaluation of customer requirements in the context of Quality Engineering & Testing, agentic AI-supported test automation using modern quality assurance approaches.
SOGETI projects:
- BMW: Development of a test strategy including test management, test automation, and provision of a rightshore delivery model.
- GEA: SAP Business Assurance and Quality Engineering for an SAP rollout including test governance, test automation, AI agent layer, and hypercare concept.
- AIXTRON: SAP S/4HANA Cloud migration explore phase with QA assessment, testable blueprint structure, staffing, and scalable Sogeti delivery approach.
- Deutsche Glasfaser: Quality Engineering & Testing for DG development squads, including ServiceNow and Salesforce, testing automation and governance.
- ERGO: RfP/proposal support for Managed Service Test Data Provisioning as well as a Jira/Atlassian rollout with assessment, target picture, MVP, rollout, and governance.
- Munich Re: Proposal and solution design in the insurance environment with a focus on test data provisioning, process analysis, compliance, and automation.
- BWI: Project/proposal context in the public/IT service environment with reference to Quality Engineering, Test Factory, and digital transformation support.
- Rolls-Royce: Proposal/project support in the Sogeti context with a focus on structured RfP analysis, solution design, and customer-oriented proposal preparation.
Alexander Schulze
Last position:
AI Consultant for AI Voice Bot System at Rudolf Hörmann GmbH & Co.KG
- Consultant for system architecture, AI agents & integration, coach for data & process logic, Graph-RAG approaches, security and data protection.
- On-premise AI solutions with high compliance and performance requirements.
- Architecture decisions, operational setup, strategic prioritization & deployment.
- Technologies: LiveKit JS SDK, LiveKit Agents, Web Audio API, JS, AudioWorklet, Loki, vLLM, Zscaler, Docker, Neo4j, MySQL, Python.
- Models: GPT-OSS 20B, Whisper large v3 turbo, Qwen3-TTS.
Patrik Garten
Last position:
Technical Lead Conversational AI at CANCOM
- Technical lead of a team developing agentic chatbot solutions (React, TypeScript, Python, FastAPI)
- Architecture design for multi-LLM dialog systems - focus on maintainability, UX, and autonomous execution
- Stakeholder alignment, CI/CD processes, and AI integration at enterprise level
Paul Webster
Last position:
Agentic AI Solution Architect at Solvd GmbH
As the Solution Architect for Agentic AI in auto claims processing, I led global customer delivery implementations, encompassing solution design and detailing, multi-tenancy, process flows, integration with third-party solutions, and localization requirements.
- Architectural Analysis: Conducted in-depth analysis of business requirements, managing requirements and creating detailed specifications.
- Service Definition: Developed comprehensive technical definitions for services and integration contracts.
- AI Process Management: Automated AI process management, focusing on analysis, optimization, and continuous improvement.
- Requirements Gathering: Facilitated requirement-gathering sessions and analyzed business processes to identify optimization opportunities.
- Agile Collaboration: Employed agile methodologies, working closely with stakeholders to ensure alignment and responsiveness.
- Technical Support: Assisted senior management with technical analyses and deliverability assessments.
Louis Guitton
Last position:
Freelance Solutions Architect and Machine Learning Engineer at Self-employed
- Develop and demonstrate solutions using GenAI software like langchain, vercel ai sdk, copilotkit
- Work with customers to understand their challenges and provide the best solutions based on open-source data products
- Build RAG and GraphRAG solutions using Neo4j, lancedb, and Postgres
- Deploy a LLMOps platform using kubernetes, terraform, helmfile, Arize phoenix, mlflow
- Architect and build data pipelines using dbt, Trino, Spark, Iceberg, Airflow, ArgoCD, terraform, kubernetes
- Delivered user-centred technical strategy for Agriculture 4.0 and precision livestock farming, helping my client secure funding from Bpifrance
- Delivered a prospecting tool for a leading French solar carport installer, using geospatial computing (GIS), speeding up the sales process
- Built digital twin architecture for solar carports and EV chargers, making real-time monitoring and smart charging possible
Siegfried-Thor Bolz
Last position:
AI Solutions Architect & Developer at E-Commerce
- Integrated LangChain middleware between AEM and SAP PIM system
- Developed a FastAPI interface for system communication
- Implemented vector embeddings for semantic product search
- Evaluated LLM models (Vertex AI/Gemini, LM Studio, Hugging Face, OpenAI) for product analysis
- Developed an AEM component to display product recommendations and integrated the recommendation API into the AEM authoring process
- Designed and implemented Pinecone vector database for product embeddings
- Optimized response times and caching strategies
- Evaluated Vertex AI Studio for LLM testing and prompt workflows
- Implemented secure API routing and access control for AI components via FastAPI and gateway validation
Kurt Rosenberg
Last position:
Lead Solution Architect (AI HealthTech) / interim CTO & Product Co-Owner at Physio-Agil Frankfurt
- General CTO responsibilities (architectural design, operational setup, external runtime product evaluation, investor buy-in, regulatory compliance).
- Software development oversight (implementation on deep-dive-in) plus workflow design.
- Product co-ownership.
- Tech/tools/frameworks: proprietary software (Java, JavaScript), Kubernetes, Postgres, MiniIO, Ollama (internal), several xAI API (external), OpenTofu (Terraform), Keycloak, Kafka, Prometheus, ELK Stack, GitHub, GitHub Workflows, Argo CD, ISO 27001, BSI-ISM, EU AI Act.
Discover over 15,000 top freelancers
AI Solution Architects statistics
Aggregated from the professional profiles of matched freelancers.
Experience
18 years
Position duration
1.7 years
Positions per freelancer
15
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Automotive
Certification focus areas
Information Technology, Business Intelligence, Product Development
Bachelor's degree or higher
91%
Master's degree or higher
70%
Doctorate
9%
Certifications per freelancer
4
Most common languages
German, English, French
Speak two or more languages
100%
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this role in Germany 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 for AI Solution Architects in Germany
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 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the role
What they design
An AI Solution Architect turns a business use case into a buildable system. They define the target architecture, choose the right model setup, and align data, security, and deployment needs. Typical deliverables include architecture blueprints, integration concepts, tech stack recommendations, and guardrails for responsible use.
- AI and machine learning architecture
- LLM and generative AI integration patterns
- Data flow, APIs, and platform design
- Governance, security, and operating model
Where they add value
Companies bring in an AI Solution Architect when an idea is stuck between strategy and implementation. That often means a new assistant, search use case, automation flow, or analytics product that needs to fit existing systems. In Germany, this is common in manufacturing, finance, logistics, insurance, and enterprise software teams that need solid technical design and clear stakeholder alignment.
Core skills
A strong AI architect understands software architecture, data engineering, model constraints, and delivery trade-offs. They can work with cloud services, vector databases, orchestration tools, and MLOps practices without overengineering the solution.
- LLMs, prompt flows, and retrieval design
- Cloud and platform architecture
- MLOps, testing, and deployment setup
- Stakeholder communication and technical decision-making
Typical projects
Freelance AI Solution Architects are often hired to set direction before a build starts, to rescue projects with unclear scope, or to review an existing design before rollout. They may define the architecture for a customer support assistant, an internal knowledge copilot, a document processing pipeline, or a model serving setup that must run reliably in production.
What strong professionals do
The best AI solution architects do not only sketch systems. They make trade-offs visible, keep security and compliance in scope, and translate business goals into practical engineering steps. They also know when a simpler design is better, especially when teams need speed, maintainability, and clear ownership.
Working with freelance experts
A freelance AI Solution Architect is a good fit when you need senior thinking without adding a permanent layer to the team. They can join remote discovery workshops, work with product and engineering leads, or support on-site sessions in Germany when alignment matters. Strong candidates leave behind decisions the team can run with, not just a concept deck.
Frequently asked questions
Need clarity? These are the questions we hear most often about AI Solution Architects.
An AI Solution Architect defines how an AI use case should work end to end. That includes the system design, data sources, model integration, deployment path, and the controls needed for security and governance. The goal is a design that engineering teams can build and operate without guesswork.
Bring in an AI architect when the scope is clear enough to design, but not yet ready for full implementation. This is useful for new AI products, internal copilots, automation initiatives, and platform reviews where senior architecture is needed fast. A freelancer is often the better choice when you need focused expertise for a defined phase.
A strong AI Solution Architect combines software architecture, data engineering, and practical knowledge of LLMs and machine learning systems. They should understand cloud services, APIs, vector search, MLOps, and the limits of different model setups. Just as important, they need to communicate clearly with product, security, and engineering teams.
A machine learning architect or solution architect may focus more narrowly on models, infrastructure, or enterprise system design. An AI Solution Architect sits between strategy and delivery and connects business needs with the full technical picture. They do not just optimize a model; they shape the whole solution around it.
In Germany, AI Solution Architects are often needed in manufacturing, logistics, finance, insurance, healthcare, and software companies. These teams usually have existing systems that must integrate with AI in a controlled way. That makes architecture decisions, data access, and governance especially important.
Most AI Solution Architect work can start remotely, especially discovery, architecture reviews, and technical design. On-site time helps when the project depends on workshop formats, stakeholder alignment, or sensitive system access. Many teams use a hybrid setup for that reason.
Look at the quality of their design choices, not just the buzzwords in their profile. A good AI Solution Architect explains trade-offs clearly, asks the right questions about data and operations, and produces a design that fits your current stack. Strong work is concrete, realistic, and ready for implementation.
Freelancers usually want a clear problem statement, the current system landscape, and the decision scope. A good AI Solution Architect assignment also defines who owns delivery, which teams are involved, and whether the focus is discovery, redesign, or implementation support. That helps them step in with the right level of depth from day one.
The average hourly rate for AI Solution Architects in Germany is 107 €, which corresponds to a daily rate of about 855 € based on an 8-hour working day.
Of the freelancers working as AI Solution Architects in Germany, 91% hold at least a Bachelor's degree, 70% hold at least a Master's degree, and 9% hold a doctorate.
On average, freelancers working as AI Solution Architects in Germany have 18 years of professional experience, with a single engagement typically lasting around 1.7 years.
The most common languages among freelancers working as AI Solution Architects in Germany are German (100%), English (100%), and French (19%).
The most common industries among freelancers working as AI Solution Architects in Germany are Information Technology (100%), Banking and Finance (58%), and Automotive (54%).
The most common business areas among freelancers working as AI Solution Architects in Germany are Information Technology (100%), Product Development (96%), and Business Intelligence (69%).
FRATCH AI Solution Architects main locations
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.
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
Get in touch with the FRATCH team and we will get back to you within 4 hours.
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Philipp Thomaschewski
FRATCH CEO
