Senior AI Engineer – Enterprise GenAI, SAP Environment

Role Overview

• Design, develop, and deploy enterprise AI and GenAI services
• Guide solutions from PoC to secure production rollout
• Build and integrate multi-agent AI systems and LLM-based products
• Work with SAP data products and underlying data architectures
• Manage ingestion, transformation, caching, and indexing workflows
• Support distributed systems and big data processing environments
• Implement CI/CD pipelines and MLOps best practices
• Automate model training, validation, testing, and deployment
• Work with Azure ML, Databricks, or AWS environments
• Implement secure API design, secrets management, and access control
• Contribute to security concept design
• Ensure observability, reliability, and compliance in AI deployments
• Collaborate with AI Product Owners, Data Scientists, and stakeholders
• Create architecture diagrams, ADRs, and technical documentation
• Ensure high-quality, well-documented codebases.

Requirements

• 5+ years of professional software engineering experience
• Strong Python expertise (mandatory)
• Experience with Node.js or Java (at least one additional language)
• Backend framework experience (FastAPI, Flask, or Django)
• Microservices architecture experience
• Docker and Kubernetes experience
• Experience with GitHub Actions, MLFlow, or similar orchestration tools
• Hands-on ETL, API integration, and model deployment experience
• Experience implementing CI/CD and MLOps in cloud environments
• Knowledge of distributed systems and big data platforms
• Experience working in Agile frameworks (Scrum, Kanban)
• Fluent English and strong problem-solving mindset.

Tech Stack

• AWS
• Azure
• Cloud
• Distributed Systems
• Django
• Docker
• ETL
• Flask
• Java
• JavaScript
• Kubernetes
• Microservices
• Node.js
• Python

Benefits

• Flexible work arrangements
• Professional development