Interim Azure AI Fullstack Engineer

Michael Page International (Deutschland) GmbH

Berlin, Germany

3 days ago

Role details

Contract type

Contract

Employment type

Part-time (≤ 32 hours)

Working hours

Regular working hours

Languages

English

Job location

Remote

Berlin, Germany

Tech stack

A/B testing

API

Artificial Intelligence

Azure

Data Security

Python

SQL Azure

Node.js

Software Architecture

Role-Based Access Control

Azure

Next.js

Search Technologies

Data Logging

Microsoft Power Automate

React

Retrieval-Augmented Generation

Large Language Models

Multi-Agent Systems

Database Optimization

Backend

Angular

Low Latency

Cosmos DB

Data Management

Machine Learning Operations

Front End Software Development

Software Version Control

Api Management

Job description

Design, develop, and operate production-grade AI solutions on the Microsoft Azure AI stack
Take end-to-end ownership across frontend, backend, data, and AI layers
Build and operate LLM/SLM-based solutions using Azure AI Foundry
Work with model catalogs, prompt flows, evaluation pipelines, and versioned deployments
Ensure performance, cost efficiency, accuracy, and reliability of production systems
Design and implement RAG (Retrieval-Augmented Generation) architectures
Utilize Azure AI Search (vector & hybrid) and Azure OpenAI Service
Implement agentic architectures and multi-agent systems (e.g., Semantic Kernel / AutoGen)
Develop frontend applications using React, Next.js, or Angular
Build backend services with Python or Node.js
Develop and operate APIs on Azure (Functions, App Service, APIM)
Implement CI/CD pipelines for AI workloads using Azure DevOps
Apply MLOps best practices (model versioning, A/B testing, controlled rollouts, monitoring)
Integrate Responsible AI mechanisms (evaluation, logging, content safety)
Work with data platforms such as Azure Data Lake, Cosmos DB, and Azure SQL
Optimize data access, embeddings, chunking, and indexing strategies
Implement security and governance standards (RBAC, Managed Identities, Private Endpoints)
Monitor and optimize token usage and overall cost

Requirements

Proven experience delivering production-grade AI applications on Azure
Strong hands-on experience with Azure AI Foundry (beyond PoCs)
Deep understanding of LLM system design, RAG architectures, and agent-based systems
Strong fullstack engineering background with the ability to work independently across all layers
Experience operating scalable AI systems with measurable impact (e.g., latency, quality, cost, adoption)
Experience with Microsoft Azure, Azure OpenAI Service, and Azure DevOps
Experience with Microsoft Copilot and Copilot Studio
Ability to clearly communicate architectural decisions and trade-offs in an enterprise environment
Experience working in security-critical and regulated environments