AI Productization Engineer

Aufgaben

About Us

Mercedes-Benz USA is responsible for the sales, marketing and service of all Mercedes-Benz and Maybach products in the United States. In our people, you will find tremendous commitment to our corporate values: 'PRIDE = Passion, Respect, Integrity, Discipline, and Execution'. Our products and employees reflect this dedication. We are looking for diverse top-notch individuals to join the Mercedes-Benz Team and uphold these hallmarks.

Job Overview

The AI Productization Engineer turns successful AI and machine learning solutions into scalable, supportable, production-ready products. This role defines the standards, integration patterns, deployment methods, and readiness processes needed to move AI capabilities from pilot to enterprise production.

The ideal candidate brings expertise in software engineering, AI delivery, enterprise integrations, and production operations. This role serves as the bridge between innovation and long-term sustainable business value.

• Lead the transition of AI and machine learning solutions from pilot to production.
• Develop reusable deployment, integration, and operational frameworks.
• Establish production readiness standards and supportability requirements.
• Define integration patterns connecting AI capabilities with enterprise business systems.
• Establish model and service versioning strategies, rollback procedures, and environment promotion workflows (dev → staging → production) with automated validation gates at each stage.
• Ensure solutions meet expectations for reliability, scalability, monitoring, and support.
• Drive consistency and repeatability across AI delivery efforts.
• Implement data validation and input contracts for AI pipelines to detect and handle upstream data changes before impacting model outputs.

• Define reference architectures and integration standards for AI products.
• Partner with engineering teams to accelerate solution deployment and adoption.
• Evaluate productization technologies, tooling, and engineering approaches.
• Contribute to architecture reviews and technical planning.
• Define API contracts for AI products, covering versioning, deprecation, rate limits, quotas, throttling, and SDK guidance.
• Define caching and performance strategies for production AI serving, including result caching, request deduplication, and edge optimizations for low latency.

• Develop standards for monitoring, incident response, deployment governance, and sustainment.
• Establish operational documentation and engineering best practices.
• Drive continuous improvement in production support processes.
• Define AI incident management processes, including classification, escalation, post-incident reviews, and handling of model-specific failures like degradation, hallucinations, and data poisoning.
• Develop AI product DR/BC plans, including failover strategies, RTO/RPO targets, and fallback modes (e.g., rules-based logic).
• Implement audit logging and traceability for AI decisions, including inference logging, input/output capture, and end to end data lineage.

• Collaborate with data science, AI engineering, architecture, and business teams.
• Provide technical mentorship and guidance to engineering teams.
• Promote engineering excellence and sustainable delivery practices.
• Provide technical mentorship and guidance across the AI Engineering organization.
• Support knowledge sharing, cross-training, and engineering excellence initiatives.

Technical Skills & Tools

Required

• Python and SQL.
• Azure Databricks and enterprise AI platforms.
• Azure or AWS cloud platforms.
• MLflow and MLOps tooling.
• API development and enterprise integration patterns.
• Docker, Kubernetes, and CI/CD pipelines.
• Production operations, observability, and monitoring.
• Enterprise application integration experience.
• Infrastructure as code (Terraform or equivalent)
• Testing frameworks and strategies for AI systems, including integration testing, performance/load testing (Locust or equivalent).

Preferred Skillset

• Salesforce integration.
• Service Now integration.
• SAP integration.
• A…