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

Benefits

• 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 with a maximum of 20% travel needs

Anforderungen

• Abschluss in Computer Science, Software Engineering, Data Science oder einem vergleichbaren technischen Fachbereich
• Überzeugende Kommunikations- und Präsentationsfähigkeiten in Deutsch (C1) und Englisch (C1), um an Workshops in beiden Sprachen teilzunehmen
• Fundierte Programmierkenntnisse in Python und modernen Backend-Frameworks
• Erfahrung im Bau von Applications unter Nutzung von AI, Machine Learning oder Generative AI Technologien
• Vertrautheit mit Retrieval-Augmented Generation (RAG) und Vector Databases
• Vertrautheit mit Cloud-Plattformen wie AWS, Azure oder GCP
• Direkter Austausch mit Enterprise-Kunden, um deren geschäftliche Herausforderungen zu verstehen und High-Impact-Opportunities für AI-driven Solutions zu identifizieren

Nice to have

• Erfahrung in der Durchführung technischer Workshops oder in der Moderation von Solution Design Sessions
• Erfahrung mit Frameworks wie LangChain, LlamaIndex oder HuggingFace
• Erfahrung in der Entwicklung von APIs, Microservices und skalierbaren Backend-Systemen, einschließlich Vector Databases
• Erfahrung mit Containerization und DevOps-Practices (Docker, CI/CD Pipelines, Kubernetes oder ähnliches)
• Erfahrung im Deployment von AI-Services in Cloud-Umgebungen
• Kenntnisse in AI Observability, Monitoring und der Evaluation von LLM-Systemen

Beispielprojekte, an denen du arbeiten könntest

• Enterprise AI Knowledge Assistants
• AI Copilots für interne Business-Tools
• Semantic Search Plattformen für Unternehmensdaten
• Document Intelligence Systeme auf Basis von LLMs
• AI Agents und Automatisierungssysteme für Enterprise Workflows