AI Engineer - Generative AI &Agentic Systems

Founded in 1999 in Vienna, the Qualysoft Group is a manufacturer-independent IT consulting and services company, which successfully provides support for its international customers with the aim of boosting their competitiveness and economic efficiency through innovative IT solutions.

Its focus is on financial services providers, telecommunications companies, the automotive industry and energy service providers. Over 400 employees in 6 subsidiaries work together to ensure state of the art solutions for our clients.

We are looking for new colleagues in Qualysoft teams for diverse projects providing continuous learning opportunities. Our common goal is to provide honesty, development and a stable background while getting to know the latest technologies. We are waiting for your application for the position below!

Design, develop, and implement agentic AI workflows and intelligent customer advisory capabilities to support customers throughout the end-to-end digital sales journey.

Build and optimize LLM-powered applications, including Retrieval-Augmented Generation (RAG) solutions and multi-agent architectures.

Develop scalable AI solutions using LangChain, LangGraph, and LangFuse.Translate complex business requirements and decision rules into reliable, scalable, and maintainable AI agent behavior.

Design and implement prompt engineering, tool/function calling, context management, memory, and structured output strategies.

Develop and integrate production-grade REST APIs using Python and FastAPI.Design and optimize retrieval solutions, including embeddings, vector search, ranking, retrieval optimization, and hybrid search.

Establish quality assurance and automated evaluation approaches for AI-driven customer interactions using tools and frameworks such as DeepEval and G-Eval.

Implement AI observability and monitoring to continuously assess application quality, reliability, and performance.

Contribute to the deployment, operationalization, and production readiness of Generative AI solutions, including CI/CD and cloud-native environments.

Apply software engineering best practices, including clean code, design patterns, automated testing, and maintainable architecture.

Collaborate closely with business stakeholders, Product Owners, developers, and other technical teams throughout design, development, testing, and production rollout.

Contribute to a cross-functional product team delivering an AI-powered Product Advisor that provides customers with personalized product recommendations and supports them from product discovery and consultation through contract completion.

Strong professional experience in Python development.

Hands-on experience designing and developing production-grade REST APIs with FastAPI.

Solid understanding of software engineering principles, including clean code, design patterns, automated testing, and scalable application architecture.P

roven practical experience developing and deploying Generative AI and LLM-powered applications.

Strong knowledge and hands-on experience with:

Prompt Engineering

Function Calling / Tool Calling

Agentic AI systems

Multi-Agent architectures

Context Management

Memory Systems

Structured Outputs

Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

Strong understanding of embeddings, vector databases, ranking, retrieval optimization, and hybrid search.

Experience with Azure AI Search or comparable search technologies.

Practical experience with relevant GenAI frameworks and tools, particularly:

LangChain

LangGraph

LangFuse

DeepEval / G-Eval

OpenAI APIs

AI observability and monitoring solutions

Experience working with data and infrastructure technologies such as:

PgVector or other vector databases

Redis

Docker

Kubernetes

CI/CD pipelines

Experience working with cloud platforms, preferably Microsoft Azure.

Ability to translate complex business requirements into robust technical solutions.

Strong communication and collaboration skills with the ability to work effectively in cross-functional product teams.