Asks for

The ad says“You act as a subject matter expert and force multiplier for NLP, LLM, and agent-based systems, supporting multiple projects in parallel, advising team members, and contributing to acquisition and technical positioning”
The ad says“You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval”
The ad says“You have experience designing cloud-based architectures and working with MLOps and deployment workflows on platforms such as Azure, AWS, or GCP”
The ad says“You have experience designing cloud-based architectures and working with MLOps and deployment workflows on platforms such as Azure, AWS, or GCP”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval”
The ad says“You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation”
The ad says“You have experience designing cloud-based architectures and working with MLOps and deployment workflows on platforms such as Azure, AWS, or GCP”
The ad says“You take end-to-end ownership of one or more focus topics in the NLP and Generative AI domain and serve as the primary technical point of contact”
The ad says“You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You have knowledge of PEFT (e.g. QLoRA), IFT, inference time tuning, post-training, embeddings, and a solid foundational knowledge of frameworks such as PyTorch”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You act as a subject matter expert and force multiplier for NLP, LLM, and agent-based systems, supporting multiple projects in parallel, advising team members, and contributing to acquisition and technical positioning”
The ad says“You have experience designing cloud-based architectures and working with MLOps and deployment workflows on platforms such as Azure, AWS, or GCP”
The ad says“You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval”
The ad says“You act as a subject matter expert and force multiplier for NLP, LLM, and agent-based systems, supporting multiple projects in parallel, advising team members, and contributing to acquisition and technical positioning”
The ad says“You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”
The ad says“You have knowledge of PEFT (e.g. QLoRA), IFT, inference time tuning, post-training, embeddings, and a solid foundational knowledge of frameworks such as PyTorch”
The ad says“You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation”
The ad says“You have knowledge of PEFT (e.g. QLoRA), IFT, inference time tuning, post-training, embeddings, and a solid foundational knowledge of frameworks such as PyTorch”
The ad says“You have knowledge of PEFT (e.g. QLoRA), IFT, inference time tuning, post-training, embeddings, and a solid foundational knowledge of frameworks such as PyTorch”
The ad says“You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation”
The ad says“You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation”
The ad says“You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval”
The ad says“You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation”

About us

statworx is a leading Data & AI Consulting and Development company in the DACH region. For more than a decade, we have been helping organizations succeed with consulting, development, and training – delivering over 1,000 successful projects for more than 100 clients across nearly every industry.

From AI strategy to implementation, we develop innovative solutions. With expertise in AI Strategy, Generative AI, Agentic AI, Data & AI Engineering, and AI Infrastructure, we support organizations throughout their entire AI transformation journey.
Our goal: Creating value from Data & AI.

Our AI Development department serves as a facilitator for Data & AI transformation. We are taking a holistic approach, from the initial evaluation of AI maturity, through the design and development of data and AI solutions, to the practical implementation and scaling of AI solutions. Through our deep expertise in Data Engineering, Data Science, Machine Learning, we ensure that our clients gain the maximum value from their data.

Your tasks

Focus: Combining deep technical expertise with project, client, and portfolio ownership

You act as a subject matter expert and force multiplier for NLP, LLM, and agent-based systems, supporting multiple projects in parallel, advising team members, and contributing to acquisition and technical positioning
You take end-to-end ownership of one or more focus topics in the NLP and Generative AI domain and serve as the primary technical point of contact
You regularly collaborate with internal stakeholders and customer representatives to ensure close alignment and effective cooperation
You present technical solution concepts, own technical communication with customers, and actively support proposal and acquisition processes
You scope, design, and oversee large-scale client projects and support high-impact initiatives with significant business relevance
You work as a technical lead on high-value customer projects and design Generative AI and NLP systems that address customer challenges in terms of performance, latency, cost, scalability, and overall system complexity
You provide professional leadership to less experienced team members, actively support their work, and offer constructive feedback and mentorship
You contribute to the development of internal products, help expand our service portfolio, and support the creation of technical marketing and thought leadership content
You continuously follow developments in NLP and AI, including new methods, tools, frameworks, and research, and apply this knowledge to projects, proposals, and customer solutions

Your profile

You have at least 7 years of solid professional experience in data science, NLP, machine learning, or generative AI, ideally in a consulting environment
You bring experience in applying common tools and methods for handling NLP use-cases such as LLM APIs (OpenAI Responses API, Bedrock, Azure AI Foundry), Frameworks (Instructor, Langchain, Langgraph, etc), HF Transformers+Tokenizers, vector databases, model deployment, inferenceservers, MCP/A2A, and dataset creation
You have experience in productive use of agent frameworks such as Langgraph, SmolAgents, OpenAI Agent SDK, CrewAI, PydanticAI and knowledge of typical LLM-based workflows such as conversational AI, RAG, information extraction, tool-calling uses, and LLM-based evaluation
You acquired knowledge of, and ideally hands-on experience with, state-of-the-art approaches such as agentic RAG, graphRAG, multi-agent workflows, text-to-2SQL, and code retrieval
You have knowledge of PEFT (e.g. QLoRA), IFT, inference time tuning, post-training, embeddings, and a solid foundational knowledge of frameworks such as PyTorch
You are able to write clean, performant, and scalable code and reliably bring complex AI systems into production
You have experience designing cloud-based architectures and working with MLOps and deployment workflows on platforms such as Azure, AWS, or GCP
You are confident interacting with customers, can communicate complex technical topics effectively, and take ownership in demanding client situations
You work in a highly structured, forward-thinking, and independent manner and remain effective in complex project environments
You have strong German and English skills, at least at the C1 level

Our offer

Data & AI at the core: Work on diverse and challenging projects with leading clients across various industries – from data-driven solutions to innovative AI applications
Professional variety & growth: Tackle complex, multifaceted questions and continuously expand your expertise in your field as well as in the broader Data & AI landscape
Continuous development: We support your methodological, professional, and personal growth through regular feedback, tailored learning opportunities, training formats, and our mentoring program
Culture & collaboration: You’ll be part of an open, diverse, and respectful work environment with flat hierarchies, short decision-making paths, and a strong sense of team spirit
Modern ways of working: We embrace an iterative, modern work culture based on clear communication, ownership, and room for new ideas and creative freedom
Transparent compensation: We offer fair, structured, and transparent salary bands that are regularly reviewed and aligned with market and performance developments
Flexible work setup: Our modern Frankfurt office serves as your main workplace – while giving you the flexibility to work remotely on a regular basis and up to four weeks per year from within the EU
Mobility & well-being: Benefit from a subsidized Germany Ticket and discounted access to sports and wellness offerings through Wellpass
Equipment & extras: High-quality IT equipment (e.g., MacBook Pro), regular team events, childcare support, and attractive employee discounts complete your package

Your application

Simply apply via the application form and attach your current CV including a description of your methodological skills. We will contact you as soon as possible. If you have any questions on your application, you can reach us at jobs@statworx.com.

What is particularly important to us is that we value the uniqueness of each person and always treat each other as equals. Different backgrounds, attitudes and ideas enrich us and form the basis of our success. That's why we welcome every application - regardless of gender, nationality, ethnic and social origin, religion, ideology, disability, age, or sexual orientation and identity.