AI Application Engineer – AI Products (LLM & RAG) (m/f/d) arbeitnow Machine Learning Reply Berlin, Berlin, Germany · 10/25/2026

Primetime; Berlin; Hybrid; EUR 70,000 - 100,000; Full time

Benefits offered by this job

Mobility package

Gym subsidy

Insurance & Pension

Savings plan

Childcare allowance

Social program

Job summary

Machine Learning Reply is seeking an AI Application Engineer to build user-facing AI applications and scalable products. You will work at the intersection of AI engineering, backend development, product development and cloud deployment to create production-ready AI systems that deliver real business value.

Responsibilities include designing AI applications, developing LLM-powered products, integrating data sources, and deploying to cloud environments using DevOps practices.

Qualifications

• Degree in Computer Science, Software Engineering, Data Science or a comparable technical field.
• Strong communication and presentation skills in German and English.
• Strong programming skills in Python and modern backend frameworks.
• Experience building AI applications using AI, ML or generative AI technologies.
• Familiarity with Retrieval-Augmented Generation (RAG) and vector databases.
• Familiarity with cloud platforms such as AWS, Azure or GCP.

Responsibilities

• Design and build AI-powered applications and product features for enterprise clients.
• Develop LLM-powered applications using Retrieval-Augmented Generation (RAG) and modern AI frameworks.
• Develop end-to-end AI products, integrating LLM APIs, enterprise data sources and backend services.
• Design scalable AI microservices and APIs to integrate AI capabilities into enterprise platforms.
• Implement vector search, embeddings pipelines and knowledge retrieval systems.
• Prototype AI product features and evolve them into production systems.
• Collaborate with product managers, designers, AI engineers and customers to develop AI solutions.
• Deploy AI systems to cloud platforms and production environments using modern DevOps practices.
• Ensure reliable, scalable, observable AI services through CI/CD, monitoring and containerized deployments.

Skills

Python

Backend frameworks

AI/ML

German and English

Education

Degree in Computer Science, Software Engineering, Data Science or a comparable technical field

Tools

AWS

Azure

GCP

Vector databases

Job description

At Machine Learning Reply, we help organizations turn cutting-edge AI technologies into real-world applications and scalable digital products.

To strengthen our team, we are looking for an AI Application Engineer who enjoys building AI-powered solutions and intelligent product features using modern machine learning and generative AI technologies.

While our GenAI Engineers focus on model development and AI architectures, AI Application Engineers focus on building user-facing AI applications and turning AI capabilities into scalable products.

In this role, you will work at the intersection of AI engineering, backend development, product development and cloud deployment, building production-ready AI systems that create real business value.

Tasks

As an AI Application Engineer, you design and build AI-powered applications and product features for enterprise clients.

Your projects may include:

Designing and developing AI applications, such as enterprise assistants, AI copilots, semantic search platforms and intelligent automation systems

Building LLM-powered applications using Retrieval-Augmented Generation (RAG) and modern AI frameworks

Developing end-to-end AI products, integrating LLM APIs, enterprise data sources and backend services

Designing scalable AI microservices and APIs to integrate AI capabilities into enterprise platforms

Implementing vector search, embeddings pipelines and knowledge retrieval systems

Rapidly prototyping AI product features and proof-of-concepts and evolving them into production systems

Collaborating closely with product managers, designers, AI engineers and enterprise customers to develop impactful AI solutions

Deploying AI systems to cloud platforms and production environments using modern DevOps practices

Ensuring reliable, scalable and observable AI services through CI/CD pipelines, monitoring and containerized deployments

Work in an open and collaborative environment within the global Reply network and build next-generation AI applications and intelligent digital products

Collaboration with interdisciplinary teams including AI engineers, software developers and data scientists across industries such as Banking, Insurance, Automotive and Retail

A very active social program including paid training, conferences, communities of practice, hackathons and Reply XChange

Monetary Benefits include: Mobility package, Gym subsidy & WellPass, Insurance & Pension Scheme, Corporate Savings Plan, KiTa and Childcare Allowance

Flexible work arrangement between home office, EU-wide workation options, on site office-work in our downtown Munich office with access to Stammstrecke, and client on site visits

Requirements

Degree inComputer Science, Software Engineering, Data Science or a comparable technical field

Convincing communication and presentation skills inGerman and English in order to participate in workshops of both languages

Strong programming skills inPythonand modern backend frameworks

Experience buildingapplications using AI, machine learning or generative AI technologies

Familiarity withRetrieval-Augmented Generation (RAG)and vector databases

Familiarity withcloud platforms such as AWS, Azure or GCP

Engaging directly with enterprise clients to understand their business challenges and identify high-impact opportunities for AI-driven solutions

Nice to have

Experience running technical workshops or facilitating solution design sessions

Experience developingAPIs, microservices and scalable backend systems, including vector databases

Experience withcontainerization and DevOps practices (Docker, CI/CD pipelines, Kubernetes or similar)

Experience with frameworks such asLangChain, LlamaIndex or HuggingFace

Experience deployingAI services in cloud environments

Knowledge ofAI observability, monitoring, and evaluation of LLM systems

Example projects you may work on

EnterpriseAI knowledge assistants

AI copilotsfor internal business tools

Semantic search platformsfor enterprise data

Document intelligence systemspowered by LLMs

AI agents and automation systemsfor enterprise workflows

This overview was written from the original listing to help you understand the role. Always confirm the specifics on the employer’s application page.