Python Developer - Generative AI / RAG

Qualysoft GmbH Python Developer - Generative AI / RAGQualysoft GmbH

Wien, Austria

4 days ago

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Role details

Contract type

Temporary contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Languages

English

Job source

devjobs.at

Tech stack

Clean Code Principles Application Programming Interfaces (APIs) Artificial Intelligence Automated Storage and Retrieval Systems Unit Testing Code Review Databases Continuous Integration Data Transformation Software Debugging Python (Programming Language) PostgreSQL

+19 more

Meta-Data Management NoSQL Software Architecture E2e Testing Search Technologies Software Engineering Data Logging Data Processing Retrieval-Augmented Generation Large Language Models Generative AI Backend Git Fastapi Integration Tests Information Technology Data Analytics GPT Software Version Control

Job description

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

Requirements

Completed degree in computer science, business informatics, data science, Artificial Intelligence or a comparable qualification, * Very good knowledge of Python and modern Python software-development practices
Very good understanding of RAG architectures, Large Language Models and Generative AI applications
Sound understanding of APIs, integration patterns and backend architectures
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
Very good written and spoken English skills
Structured, independent and solution-oriented way of working
Strong communication and collaboration skills, * At least 5+ years of professional experience in software development with Python
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
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
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