AI Productization Engineer

Mercedes-Benz USA, LLC

Mercedes-Benz USA, LLC Corporate Headquarters, Atlanta, GA (On-site)

Job Type Full-time

Experience Senior

Posted 1 week 4 days ago

On-site Senior Level

About Us

Mercedes-Benz USA is responsible for the sales, marketing and service of all Mercedes-Benz and Maybach products in the United States. We are looking for diverse, high-caliber individuals to join the Mercedes-Benz Team.

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.

Responsibilities

AI Productization & Production Readiness (60%)

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 with automated validation gates.
Ensure solutions meet expectations for reliability, scalability, monitoring, and support.
Implement data validation and input contracts for AI pipelines.

Architecture & Integration Leadership (20%)

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.
Define API contracts, caching strategies, and performance approaches for production AI serving.

Operational Excellence (10%)

Develop standards for monitoring, incident response, deployment governance, and sustainment.
Define AI incident management processes and model-specific failure handling.
Develop AI disaster recovery and business continuity plans.
Implement audit logging and traceability for AI decisions.

Collaboration & Technical Leadership (10%)

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

Required Skills and Qualifications

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.
Infrastructure as code, such as Terraform.
Testing frameworks and strategies for AI systems.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.
8+ years of software engineering, ML engineering, platform engineering, or AI engineering experience.
Experience deploying AI or ML capabilities into production environments.
Experience designing scalable enterprise integration solutions.
Strong understanding of operational support, production delivery, communication, and stakeholder management.

Preferred Qualifications

Salesforce, ServiceNow, or SAP integration.
Azure API Management or AWS API Gateway.
Apache Airflow or Databricks Workflows.
OpenTelemetry and advanced observability tooling.
Experience supporting AI and agent-based solutions in production.
Responsible AI tooling and governance practices.
Master’s degree in a related field.

Additional Information

The position requires regular collaboration with business, technology, and external partner teams across multiple time zones. Some travel is required. This role is part of MBUSA’s Data Insights & AI organization.