AI Productization Engineer

Aufgaben About UsMercedes-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 OverviewThe 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.ResponsibilitiesAI Productization & Production Readiness 60Lead 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.Architecture & Integration Leadership 20Define 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.Operational Excellence 10Develop 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 DRBC plans including failover strategies RTORPO targets and fallback modes e.g. rules-based logic.Implement audit logging and traceability for AI decisions including inference logging inputoutput capture and end to end data lineage.Collaboration & Technical Leadership 10Collaborate 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. Qualifikationen Technical Skills & ToolsRequiredPython 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 CICD pipelines.Production operations observability and monitoring.Enterprise application integration experience.Infrastructure as code Terraform or equivalentTesting frameworks and strategies for AI systems including integration testing performanceload testing Locust or equivalentPreferred SkillsetSalesforce integration.ServiceNow integration.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.Caching technologies Redis Azure Cache CDNResponsible AI tooling for production including fairness monitoring bias detection andexplainability frameworks e.g. SHAP LIME Azure Responsible AI.Modern API patterns GraphQL gRPC WebSockets for high-performance and real-time AI product interfaces.QualificationsRequiredBachelors degree in Computer Science Engineering Information Systems or 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 and production delivery.Strong communication and stakeholder management skills.Preferred ExperienceMasters degree in Computer Science Engineering AIML or related field.Experience building reusable engineering frameworks and productization standards.Experience operating in regulated or compliance-sensitive environments.Familiarity with Responsible AI and AI governance practices.Additional InformationPosition requires regular collaboration with business technology and external partner teams across multiple time zones.Some travel required for team partner and business engagements.This role is part of MBUSAs Data Insights & AI organization and contributes to the companys long-term AI strategy and operating model.EEO StatementMercedes-Benz USA is committed to fostering an inclusive environment that appreciates and leverages the diversity of our team. We provide equal employment opportunity EEO to all qualified applicants and employees without regard to race color ethnicity gender age national origin religion marital status veteran status physical or other disability sexual orientation gender identity or expression or any other characteristic protected by federal state or local law.