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Ai Rag Jobs in Wisconsin (NOW HIRING)

$52.75 - $72.75/hr

For a challenging AI and data transformation project with a client in the telecommunications sector, we are looking for an experienced Python Developer - Generative AI / RAG (m/f/d) in Vienna. The ...

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications ... Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor)

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications ... Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor)

AI Engineer

Watertown, WI · On-site +1

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications ... Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor)

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications ... Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor)

AI Engineer

Watertown, WI · On-site +1

VAS is seeking an AI Engineer to lead building of scalable real-time production grade applications ... Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor)

Python AI Developer

Green Bay, WI · On-site

$49 - $67.25/hr

This individual will not just be wrapping APIs; they will be building the memory layers, RAG pipelines, and ontological structures that allow our AI to serve as a true co-pilot for logistics ...

This AI/ML Engineer role sits at the center of that transformation. You will do two things in ... Implement RAG architectures, agentic workflows, and prompt engineering patterns for production ...

AI Engineer

Glendale, WI · On-site +1

This AI/ML Engineer role sits at the center of that transformation. You will do two things in ... Implement RAG architectures, agentic workflows, and prompt engineering patterns for production ...

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Build and operationalize generative AI applications using large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation that real people across the business ...

Senior AI Engineer

Middleton, WI · On-site

$107K - $147K/yr

Build and operationalize generative AI applications using large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation that real people across the business ...

Senior AI Engineer

Middleton, WI

$107K - $147K/yr

Build and operationalize generative AI applications using large language models (LLMs), retrieval-augmented generation (RAG), copilots, and intelligent automation that real people across the business ...

Principal AI Engineer

Milwaukee, WI · On-site

$197K - $208K/yr

Principal AI Systems Architect (Contract Engagement) Role Overview We are seeking a Principal AI ... Architect production-scale RAG (Retrieval-Augmented Generation) pipelines, vector database ...

RAG-Applikationen) in Microsoft Azure Aufbau, Orchestrierung und Weiterentwicklung von AI-Agenten und Multi-Agenten-Systemen Einsatz und Integration von Model Context Protocols (MCPs) Aufnahme ...

Experience building RAG-based systems, vector databases, and semantic search architectures. * Demonstrated ability to lead large-scale AI initiatives and influence technical strategy. * Deep ...

Experience building RAG-based systems, vector databases, and semantic search architectures. * Demonstrated ability to lead large-scale AI initiatives and influence technical strategy. * Deep ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI researcher?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

What is an AI RAG?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

What are common challenges faced by AI RAG engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What are popular job titles related to Ai Rag jobs in Wisconsin? For Ai Rag jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Ai Rag jobs in Wisconsin look for? The top searched job categories for Ai Rag jobs in Wisconsin are:
What cities in Wisconsin are hiring for Ai Rag jobs? Cities in Wisconsin with the most Ai Rag job openings:
Infographic showing various Ai Rag job openings in Wisconsin as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Python Developer - Generative AI / RAG (m/f/d)

Qualysoft

Hybrid

$52.75 - $72.75/hr

Contractor

Posted 16 days ago


Job description

For a challenging AI and data transformation project with a client in the telecommunications sector, we are looking for an experienced Python Developer - Generative AI / RAG (m/f/d) in Vienna.
The focus of the role is on the development of modern, data-driven AI applications and production-ready Retrieval-Augmented Generation solutions. We are looking for an experienced Python developer with a strong analytical mindset who can design, implement and optimize scalable backend services, data-processing workflows and end-to-end RAG pipelines.
You will take on a central role in the technical implementation of modern AI use cases and support the client in integrating Large Language Models and RAG based applications into existing data, cloud and system landscapes. You will work closely with AI architects, data scientists, software developers, business departments and technical stakeholders.
You can expect an innovative project environment with high technological relevance, international stakeholders and modern AI, data and cloud technologies.
 
440 - 480 a day
Conditions
Location: Vienna
Start: ASAP
Duration: 12 months+ option for extension
Capacity: 100 %
Working model: Hybrid, 2 days per week on site in Vienna
Project language: English
 
Your Tasks
  • Development and implementation of scalable Python applications, backend services and AI-based solutions
  • Design, development and optimization of complete Retrieval-Augmented Generation pipelines
  • Implementation of document ingestion and data-processing workflows
  • Development of suitable document parsing, preprocessing, chunking and metadata strategies
  • Generation, management and optimization of embeddings
  • Implementation of semantic search, vector search and hybrid search solutions
  • Integration and management of vector databases and retrieval systems
  • Development and optimization of retrieval and reranking mechanisms
  • Implementation of prompt construction, prompt templates and context-management strategies
  • Integration of Large Language Models for reliable and context-based answer generation
  • Implementation of citation handling, source attribution and traceability mechanisms
  • Development and integration of APIs and backend interfaces
  • Integration of AI applications into existing IT, data, database and cloud landscapes
  • Design and implementation of data-driven evaluation processes for RAG and AI solutions
  • Analysis and improvement of retrieval quality, answer quality, relevance and system performance
  • Development of automated unit, integration and end-to-end tests
  • Implementation of logging, monitoring, error handling and observability mechanisms
  • Creation of technical documentation and development standards
  • Application of professional software-development practices, including version control, code reviews and CI/CD
  • Collaboration with AI architects, data scientists, developers, business departments and other technical stakeholders
  • Support of AI use cases from technical conception through implementation to productive operation
Your Profile
  • At least 5+ years of professional experience in software development with Python
  • Very good knowledge of Python and modern Python software-development practices
  • Proven experience in the development of APIs, backend services and data-processing applications
  • Practical experience in the development and implementation of Retrieval-Augmented Generation solutions
  • Very good understanding of RAG architectures, Large Language Models and Generative AI applications
  • Experience with document ingestion, document parsing, preprocessing, chunking and metadata management
  • Experience with embeddings, semantic search, vector search, retrieval and reranking
  • Experience with vector databases such as Qdrant, Weaviate, Pinecone, Milvus, Chroma or PostgreSQL with pgvector
  • Experience with RAG and LLM frameworks such as LangChain, LlamaIndex or comparable technologies
  • Experience with relational and/or NoSQL databases
  • Sound understanding of APIs, integration patterns and backend architectures
  • Experience with Git and professional version-control workflows
  • Experience with unit testing, integration testing and automated software testing
  • Experience with logging, monitoring, debugging and production software operations
  • Knowledge of clean code principles, software architecture and maintainable application design
  • Strong data-driven and analytical mindset
  • Ability to evaluate technical solutions based on measurable quality, performance and business requirements
  • Completed degree in computer science, business informatics, data science, Artificial Intelligence or a comparable qualification
  • Very good written and spoken English skills
  • Structured, independent and solution-oriented way of working
  • Strong communication and collaboration skills
Nice to Have
  • Experience in the telecommunications environment
  • Experience with cloud technologies such as AWS, Microsoft Azure or Google Cloud
  • Experience with Docker, Kubernetes and CI/CD pipelines
  • Experience with Python frameworks such as FastAPI, Flask or Django
  • Knowledge of MLOps, LLMOps or AI platform architectures
  • Experience with the evaluation of RAG systems, including retrieval quality, answer relevance, groundedness, hallucination detection and citation accuracy
  • Experience with hybrid search, knowledge graphs or graph-based RAG architectures
  • Experience with agent-based AI systems and tool-using Large Language Models
  • Experience with open-source and commercial Large Language Models
  • Experience with LLM observability, tracing and evaluation platforms
  • Knowledge of AI governance, Responsible AI, data protection, security and compliance requirements
  • Experience in international and interdisciplinary project environments
  • Relevant AI, cloud or software-development certifications
 
What You Can Expect
  • Participation in an innovative AI and data transformation project in the telecommunications environment
  • Exciting technological environment with a focus on Python, Generative AI and Retrieval-Augmented Generation
  • Opportunity to develop and operate modern, production-ready AI applications
  • High level of personal responsibility and opportunities to shape technical solutions
  • Collaboration with international stakeholders and technical expert teams
  • Hybrid working model with 2 days per week on site in Vienna
  • Opportunity to actively shape scalable RAG and AI architectures
  • Use of modern Python, LLM, vector database and cloud technologies
  • Long-term relevant project environment with high strategic importance
Interested?
Please send us your current CV, including your availability and hourly rate expectations. We look forward to hearing from you.
You are welcome to contact me by email or via LinkedIn.
Elena Kahraman
Thank you for your understanding.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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