LangSmith Experts in Berlin
in minutes from over 15,000 CVs with the power of AI.Hire experts who use LangSmith to trace LLM calls, review prompts and outputs, and improve agent workflows. They bring clear debugging, evaluation, and observability to complex AI systems, with fast, precise matching from vetted, available freelancers.
Meet FRATCH Experts in Berlin, who have recently used LangSmith
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.
Hamza K.
Last position:
Academic Research Contributor in Health Sector (Volunteer)
- 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.
Viktor S.
Last position:
AI Engineer (Freelance) at Empion
Enterprise AI content categorization and AI-powered web research.
- Built multi-LLM evaluation framework with annotated data
- Iterated LLM error rates based on annotated datasets
- Implemented AI-powered web research pipeline Stack: LLM, evals, OpenRouter, Python, Node.js, TypeScript, React
Julien L.
Last position:
MLOps Engineer at SAMGEN
- Building and scaling cloud infrastructure on GCP to support a SaaS platform for industrial clients
- Designing and implementing a data-driven DevOps pipeline for streamlined deployment and CI/CD workflows
- Collaborating with Data Science team on MLOps workflow to automate integrated retraining
Shriya S.
Last position:
Product Manager at passify
- Leading the setup of Passify’s internal automation and risk management portal, connecting workflows across teams through SharePoint and Power Automate.
- Moderating retrospective workshops and creating PRDs and design tickets during PDLC.
- Supporting ISO 27001 documentation and compliance, focusing on customer support, user registration, and internal communication processes.
- Helping align design, development, and operations in a modular design cycle, ensuring each release meets both business and user needs.
- Contributing to feature planning and validation for subcontractor flows, training dashboards, and terminal portal improvements.
Muskan V.
Last position:
AI Engineer at Sagas IT Analytics
- Built an AI Research Assistant with RAG, LangChain, LangGraph, and OpenAI LLMs integrated with vector search; cut research time by 30%.
- Designed custom retrieval workflows with LlamaIndex, building a ReAct-style agent for dynamic chunking; improved query accuracy by 18%.
- Researched and optimized embedding strategies, reducing retrieval cost/query by 15%.
- Developed RAG evaluation frameworks using RAGAS and Langsmith with custom datasets; improved coverage by 40%.
- Fine-tuned LLMs (LLaMA 2 on Vertex AI with custom inference containers, dynamic batching, and quantization); reduced inference latency by 25%.
- Integrated AI agents in LangGraph with short-term & long-term memory (Mem0); increased task completion rate by 20%.
- Created schema-aware synthetic data generators; fine-tuned downstream models achieving +12% F1 score.
Kaan D.
Last position:
IT Consultant at Tensora GmbH
Discover over 15,000 top freelancers
Statistics of experts using LangSmith
Aggregated from the professional profiles of matched freelancers.
Experience
10 years
Position duration
1.6 years
Positions per freelancer
9
Top business areas
Information Technology, Product Development, Research and Development
Top industries
Information Technology, Professional Services, Healthcare
Bachelor's degree or higher
100%
Master's degree or higher
57%
Certifications per freelancer
1
Most common languages
German, English, Arabic
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 Berlin 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 Berlin using LangSmith
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.
LangSmith 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%)
- Professional Services (71%)
- Healthcare (57%)
- Energy (43%)
- Banking and Finance (43%)
- Media and Entertainment (43%)
- Retail (43%)
- Education (29%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What LangSmith does
LangSmith is the observability and evaluation layer in the LangChain ecosystem. It helps teams trace model calls, inspect prompt flows, compare outputs, and understand where an LLM application breaks. Companies use it to make chatbots, agents, retrieval pipelines, and workflow-heavy products easier to debug and trust.
Where it fits
LangSmith is useful when LLM behavior is hard to predict and small prompt changes affect results. It gives specialists a place to inspect runs, compare versions, and review traces across model calls, tools, and chains. It is often used alongside LangChain, OpenAI, vector stores, and API-based services.
Typical work
- Trace prompt and model behavior across chains and agents
- Build evaluation sets for regression testing
- Review retrieval quality and tool calls
- Compare prompt versions before release
- Set up feedback loops for production runs
When to bring in help
Teams usually look for LangSmith expertise when LLM features are moving into production and failures are hard to reproduce. It is also useful after a prompt rewrite, a new agent design, or a retrieval change. In Berlin, this often matters for product teams working in English while keeping reviews and documentation clear for local stakeholders.
What strong specialists do
Strong professionals know how to connect LangSmith to real application flows, not just demo notebooks. They define useful evals, read traces with context, and turn noisy outputs into clear next steps. Good specialists also understand prompt design, structured outputs, RAG, and how to keep observability practical for the team.
Ecosystem and signals
LangSmith work often sits close to LangChain projects, Python services, and cloud deployments. Companies benefit from expertise when they need better traceability, repeatable tests, or cleaner handoffs between product, ML, and software teams. If a team asks why an agent answered poorly, LangSmith helps show where the issue started.
Frequently asked questions
The facts hiring teams ask for most often when it comes to LangSmith.
LangSmith is used to trace LLM runs, inspect prompts and outputs, and evaluate how an application behaves in real use. Teams rely on it for debugging chatbots, agents, and retrieval flows when model responses are inconsistent or hard to explain.
LangSmith is the observability and evaluation layer, while LangChain is the framework used to build many LLM workflows. In practice, teams often use them together, and they may also compare LangSmith with logging tools or custom dashboards when they want clearer traces and repeatable evaluations.
A strong LangSmith specialist usually knows prompt design, Python, API integration, and evaluation methods for LLM systems. Useful adjacent skills include LangChain, retrieval-augmented generation, structured outputs, and production debugging across model providers.
LangSmith expertise becomes valuable when simple prompt testing is no longer enough. If an agent, chatbot, or RAG workflow is already live or close to launch, a specialist can help trace failures, compare versions, and build evaluations that catch regressions early.
Yes, LangSmith work is often done remotely because the core tasks are tracing, evaluation, and integration. In Berlin, many teams still prefer a short on-site start for product alignment, then continue online with clear traces and written feedback.
A good LangSmith freelancer shows how they turn traces into decisions, not just screenshots. Look for clear eval design, practical debugging steps, and the ability to explain why a prompt, retrieval step, or tool call led to a bad result.
No, LangSmith is strongest in the LangChain ecosystem, but it can also help with broader LLM applications that use direct API calls. The main question is whether you need tracing, evaluation, and run review for a model-driven workflow, regardless of the exact framework.
Before bringing in LangSmith help, prepare a few failing examples, the current prompt or chain, and any notes on expected behavior. That gives the specialist enough context to set up traces, build meaningful evaluations, and focus on the parts that matter most.
The average hourly rate of freelancers in Berlin, Germany who have used LangSmith in their recent projects is 65 €, which corresponds to a daily rate of about 523 € based on an 8-hour working day.
Of the freelancers in Berlin, Germany who have used LangSmith in their recent projects, 100% hold at least a Bachelor's degree and 57% hold at least a Master's degree.
On average, freelancers in Berlin, Germany who have used LangSmith in their recent projects have 10 years of professional experience, with a single engagement typically lasting around 1.6 years.
The most common languages among freelancers in Berlin, Germany who have used LangSmith in their recent projects are German (100%), English (100%), and Arabic (14%).
The most common industries among freelancers in Berlin, Germany who have used LangSmith in their recent projects are Information Technology (100%), Professional Services (71%), and Healthcare (57%).
The most common business areas among freelancers in Berlin, Germany who have used LangSmith in their recent projects are Information Technology (100%), Product Development (100%), and Research and Development (86%).
Main locations of FRATCH Experts, who have recently used LangSmith
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
