$52.75 - $72.75/hr
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 ...
$52.75 - $72.75/hr
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 ...
Pinecone Vector Databases information
What is a Pinecone vector database?
A Pinecone Vector Database is a cloud-based service designed to efficiently store, index, and search high-dimensional vector data, such as embeddings generated by machine learning models. It enables fast similarity search, making it ideal for use cases like semantic search, recommendation systems, and AI-powered applications. Pinecone handles the complexity of scaling and managing vector data, so developers can focus on building intelligent applications without worrying about infrastructure.
What are the key skills and qualifications needed to thrive as a Pinecone vector database engineer, and why are they important?
To thrive as a Pinecone Vector Database Engineer, you need a strong background in computer science, data engineering, and experience with large-scale distributed systems, often supported by a relevant degree or equivalent experience. Proficiency in Python, REST APIs, cloud platforms (AWS, GCP), and vector search technologies, along with familiarity with Pinecone’s SDK and database management, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you collaborate with cross-functional teams and deliver scalable solutions. These skills ensure robust database performance, efficient data retrieval, and successful integration of vector search capabilities into real-world applications.
What are some common challenges faced by engineers working with Pinecone vector databases, and how can they be addressed?
Engineers working with Pinecone Vector Databases often encounter challenges such as optimizing vector search performance at scale, ensuring data consistency across distributed systems, and integrating the database with various machine learning pipelines. Addressing these challenges typically involves tuning indexing parameters, monitoring resource utilization, and collaborating closely with data scientists to understand retrieval requirements. Regularly reviewing documentation and participating in community forums can also help engineers stay current with best practices and new features.
What is the difference between Pinecone Vector Databases vs Data Engineers?
| Aspect | Pinecone Vector Databases | Data Engineers |
|---|---|---|
| Primary Role | Managing and deploying vector database solutions for AI/ML applications | Designing, building, and maintaining data pipelines and infrastructure |
| Skills & Certifications | Knowledge of vector databases, cloud platforms, programming (Python, SQL) | Data modeling, ETL processes, cloud services, programming (Python, Java) |
| Work Environment | Tech companies, AI startups, cloud providers | Data-driven organizations, tech firms, finance, healthcare |
While Pinecone Vector Databases specialists focus on deploying and managing vector database solutions for AI applications, Data Engineers build and maintain the data infrastructure that supports these systems. Both roles require programming skills and familiarity with cloud platforms, but their core responsibilities differ: one centers on database management, the other on data pipeline development.
What are popular job titles related to Pinecone Vector Databases jobs in Wisconsin? For Pinecone Vector Databases jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Pinecone Vector Databases jobs in Wisconsin look for? The top searched job categories for Pinecone Vector Databases jobs in Wisconsin are:
$52.75 - $72.75/hr
Contractor
Posted 17 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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