Function Calling Experts in Berlin
to connect AI with real systems, matched in minutesWork with specialists who connect language models to business tools, define reliable function schemas, and build production-ready agent workflows. FRATCH matches you quickly with vetted, available freelancers whose experience fits your project.
Meet FRATCH Experts in Berlin, who have recently used Function Calling
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.
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.
Marvin M.
Last position:
Co-founder & CTO · Freelance Software Engineer (AI & SaaS) at Self-employed
- Self-employed · Berlin, Germany
- Co-founded the company and own the entire technical side: product architecture, backend, frontend, infrastructure and operations.
- Designed and built the Automated Booking System (ABS) as well as the core platform and payment logic.
- Development of AI-powered SaaS products, from architecture through backend and frontend to production operation.
- Technical consulting on product architecture, data protection and permissible automation.
- Building, running and monetising my own API products for AI agents, each available as a REST interface and as an MCP server.
- Full ownership of architecture, infrastructure, billing, legal texts and go-to-market.
Hamza K.
Last position:
Academic Research Contributor in Health Sector (Volunteer) at n/a
- Acted as technical consultant to optimize multi-layer ensemble models combining ResNet, CNN-BiGRU-Attention, and XGBoost.
- Guided implementation of a Logistic Regression meta-learner to solve class imbalance problems, achieving 92.86% accuracy and 0.9644 AUC on PTB-XL and Chapman-Shaoxing datasets.
Murad H.
Last position:
Founder & Technical Lead at Hubpoint.Ai
- Founded an AI-powered scheduling and business-management SaaS for SMBs, owning technology strategy, architecture, product development, UX, billing and go-to-market execution.
- Architected and shipped a multi-tenant platform with REST APIs, RBAC, CRM, billing and notifications, powering the manager dashboard, admin console, booking experience and iOS/Android applications.
- Led and mentored 7 software engineers, 1 DevOps engineer, 1 QA engineer and 1 UX/UI designer, while remaining hands-on across backend, frontend and product delivery.
- Built AI voice and chat agents using Python/FastAPI, OpenAI and Anthropic APIs, RAG, pgvector and tool calling; integrated Twilio, Google Calendar/Meet, Stripe and Firebase.
- Owned production infrastructure and automated delivery across separate environments using Docker, Nginx, GitHub Actions and Grafana; represented the company at accelerators and international startup events.
Selected stack: Python, FastAPI, Node.js, Vue 3, React/Next.js, React Native, PostgreSQL, Redis, Docker
Haseeb Z.
Last position:
Senior Data Scientist at WPP MEDIA
- Designed and deployed enterprise Retrieval-Augmented Generation (RAG) applications using LangChain, LangGraph, vector databases, embeddings, and open-source LLMs served through vLLM on GCP GPU infrastructure.
- Built agentic AI workflows using LangGraph with planning, reasoning, tool execution, persistent memory, session management, and Human-in-the-Loop approval mechanisms.
- Developed LLM-powered automation systems integrating BigQuery, SQL pipelines, and external advertising APIs including Meta, TikTok, Amazon, Snapchat, Google, and Pinterest, reducing manual operational workflows.
- Architected multi-agent AI systems for enterprise analytics and decision-support workflows, enabling autonomous task execution and intelligent data interactions.
- Implemented retrieval optimization strategies including multi-retriever architectures, semantic search, context optimization, and query improvement techniques, improving response relevance by approximately 40%.
- Engineered structured prompting strategies, function-calling schemas, and validation workflows to improve reliability of multi-step LLM applications.
- Designed scalable AI services using Python, FastAPI, Cloud Run, Pub/Sub, BigQuery, Docker, and cloud-native deployment architectures.
Discover over 15,000 top freelancers
Statistics of experts using Function Calling
Aggregated from the professional profiles of matched freelancers.
Experience
11 years
Position duration
1.3 years
Positions per freelancer
8
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Banking and Finance, Healthcare
Certification focus areas
Information Technology, Product Development, Business Intelligence
Bachelor's degree or higher
100%
Master's degree or higher
83%
Certifications per freelancer
3
Most common languages
English, German, Azerbaijani
Speak two or more languages
83%
Based on our profile pool as of 26 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 Function Calling
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 26 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Function Calling 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 (50%)
- Healthcare (50%)
- Education (33%)
- Energy (33%)
- Media and Entertainment (33%)
- Retail (33%)
- Advertising (17%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Function Calling does
Function Calling lets a language model request a structured action from an external system instead of returning text alone. The application validates the request, runs the selected function, and sends the result back for a useful response. It is commonly used to connect conversational AI with business data and operations.
Where it is used
Companies use Function Calling to make AI assistants perform controlled actions across internal and customer-facing systems.
- Query product, account, or support data
- Create tickets, bookings, orders, or workflow tasks
- Call search, payment, CRM, and analytics services
- Coordinate multi-step agent workflows
Ecosystem and tooling
Strong specialists work across model APIs such as OpenAI function calling and tool calling, as well as compatible interfaces from other model providers. They define JSON schemas, manage tool registries, validate arguments, and connect calls to REST APIs, databases, queues, and server-side application code.
Observability and testing matter as much as integration. Useful tooling includes schema validators, structured logging, tracing, permission layers, mock tools, and evaluation suites for tool selection and response quality.
When companies need expertise
Freelance expertise is valuable when a prototype must become a dependable product or when an existing assistant needs access to protected company systems.
- Design a safe tool-calling architecture
- Convert vague prompts into precise schemas
- Add authentication, authorization, and approval steps
- Reduce failed calls, invalid arguments, and unwanted actions
In Berlin, specialists may support AI products in finance, mobility, commerce, health, and industrial operations. Remote collaboration works well when API ownership, environments, and review processes are clearly defined.
What strong professionals deliver
The best professionals treat Function Calling as an application design problem, not a prompt-only task. They separate model decisions from execution, keep tools narrow and auditable, handle retries and timeouts, and design clear fallbacks when a model cannot complete an action.
They also understand data protection, secret management, rate limits, and human approval for sensitive operations. Their deliverables can include tool schemas, integration services, test cases, monitoring dashboards, and practical documentation for the internal team.
How to assess fit
Review examples that show complete flows from user request to validated tool result. Ask how the specialist handles malformed arguments, ambiguous intent, unavailable services, duplicate requests, and permissions.
A good technical discussion should cover model choice, schema versioning, error handling, evaluation methods, and operational ownership. For Berlin teams, confirm whether collaboration requires on-site workshops or can be handled remotely, and align on English or German communication needs.
Frequently asked questions
Not sure where to start with Function Calling? These answers cover the essentials.
Function Calling allows a language model to request structured actions from software tools. Companies use it for assistants that retrieve data, update records, trigger workflows, or combine several services while keeping execution inside their application.
Function Calling gives a model a defined interface for requesting actions rather than relying on free-form text and custom parsing. The surrounding application still validates arguments, enforces permissions, executes the tool, and decides what result to show.
Function Calling is a capability for connecting a model to tools, while an agent framework usually adds orchestration, memory, planning, state handling, or tracing. A project may use direct model APIs for a small workflow or adopt a framework when many tools and execution paths must be coordinated.
Function Calling work benefits from strong API integration, backend application design, JSON Schema, authentication, database access, and observability skills. Experience with prompt design, retrieval systems, evaluation, and cloud deployment is also useful when the integration runs in production.
Function Calling can be introduced by a specialist familiar with model APIs and structured data, but production systems require deeper application experience. The right level depends on tool sensitivity, integration complexity, traffic, and whether the system can act without human approval.
Function Calling projects are often suitable for remote collaboration because the main work happens in repositories, API environments, and shared evaluation tools. On-site sessions can still help with domain discovery, security reviews, and alignment with teams that own sensitive systems.
Function Calling is implemented well when tools have narrow purposes, strict schemas, clear permissions, and observable execution. Quality also shows in reliable handling of invalid inputs, timeouts, retries, duplicate actions, ambiguous requests, and unavailable services.
Function Calling specialists should be able to explain how they test tool selection and argument generation without judging the system only by fluent responses. Ask for a concrete approach to schema design, security, failure handling, monitoring, and handover to the team that will operate the integration.
The average hourly rate of freelancers in Berlin, Germany who have used Function Calling in their recent projects is 92 €, which corresponds to a daily rate of about 734 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used Function Calling in their recent projects, 100% hold at least a Bachelor's degree and 83% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used Function Calling in their recent projects have 11 years of professional experience, with a single engagement typically lasting around 1.3 years.
The most common languages among freelancers in Berlin, Germany who have used Function Calling in their recent projects are English (100%), German (83%), and Azerbaijani (17%).
The most common industries among freelancers in Berlin, Germany who have used Function Calling in their recent projects are Information Technology (100%), Banking and Finance (50%), and Healthcare (50%).
The most common business areas among freelancers in Berlin, Germany who have used Function Calling in their recent projects are Information Technology (100%), Product Development (100%), and Business Intelligence (67%).
Main locations of FRATCH Experts, who have recently used Function Calling
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.
Countries:
Berlin 
Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg Request a free demo
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Philipp Thomaschewski
FRATCH CEO
