Role Overview

We are seeking a Full Stack Applied AI Engineer to build and deliver production grade, AI powered applications. This role focuses on applied and agentic AI, integrating LLMs into real-world full stack systems using modern frontend, backend, and Azure cloud technologies.

The ideal candidate is hands on, delivery oriented, and experienced in AI assisted/agentic coding, full stack development, and cloud deployments.

Key Responsibilities

Design and develop AI enabled full stack applications across web and mobile platforms
Build guided / agentic AI solutions using LLMs, prompt engineering, RAG, and tool/function calling
Develop frontend applications using React and/or Flutter
Build secure, scalable backend APIs and services using C# / .NET
Integrate AI services into business workflows and user interfaces
Deploy and operate applications on Microsoft Azure
Implement CI/CD pipelines and follow DevOps best practices
Ensure code quality, performance, security, and maintainability
Collaborate closely with product, UX, and business stakeholders

Required Skills

Frontend

React (mandatory)
Flutter (preferred)

Backend

C# / .NET
REST API design and integration

Applied AI

Hands on experience with LLMs and prompt engineering
Experience building or integrating agentic AI workflows
Familiarity with RAG, vector databases, LangChain like frameworks

Cloud & DevOps

Microsoft Azure (App Services, Azure OpenAI, Functions, Storage, etc.)
Azure DevOps CI/CD
Docker (AKS is a plus)

Good to Have

Experience with Azure OpenAI or similar AI platforms
Python or Node.js for AI orchestration
Experience integrating AI into enterprise/business systems
Exposure to AI assisted development tools and workflows

Soft Skills

Strong problem solving and ownership mindset
Ability to translate business problems into practical AI solutions
Clear communication with technical and non technical stakeholders

Erforderliche Kompetenzen

ReactFlutterC# / .NETREST API design and integrationLarge Language Models and prompt engineeringAgentic AI workflows and tool/function callingRetrieval-Augmented Generation (RAG) and vector databasesLangChain-like frameworksMicrosoft Azure (App Services, Functions, Storage, Azure OpenAI)Azure DevOps CI/CDDocker and containerization (AKS familiarity)Python or Node.js for AI orchestrationCI/CD and DevOps best practices (implementation and operation)Software quality, performance, security, and maintainabilityCross-functional collaboration and stakeholder communication

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