Applied AI/ML Solutions Engineer

Job Overview The Applied ML/AI Solutions Engineer is responsible for designing, building, and delivering AI-powered solutions that drive measurable business value across Mercedes- Benz USA. This role develops copilots, intelligent assistants, agent-based solutions, and AI-enabled business processes that solve real-world business challenges The ideal candidate combines strong software engineering expertise, modern AI development experience, and solution architecture skills to deliver scalable, production- ready capabilities. This role works closely with data scientists, AI engineers, architects, and business stakeholders to transform opportunities into operational AI solutions Responsibilities Applied AI Solution Delivery (60%) • Design, develop, and deploy AI-powered applications, copilots, assistants, and agent-based solutions • Translate business requirements into scalable technical architectures and working solutions • Integrate AI capabilities with enterprise applications, APIs, and operational systems • Deliver production-ready solutions that meet standards for performance, reliability, security, and supportability • Leverage established AI platform, LLMOps, and productization frameworks to accelerate delivery • Contribute code, technical leadership, and best practices across the AI solution portfolio Solution Architecture & Design (20%) • Define solution architectures and technical designs for AI initiatives • Evaluate technologies, frameworks, and implementation approaches • Align solutions with enterprise architecture, security, and governance standards • Support planning, estimation, and technical execution activities Engineering Excellence & Innovation (10%) • Establish and uphold standards for code quality, testing, documentation, and operational readiness • Evaluate emerging AI technologies and development approaches • Contribute reusable patterns that improve delivery efficiency and consistency Collaboration & Technical Leadership (10%) • Partner with business stakeholders, product teams, and engineering teams to drive successful outcomes • Mentor engineers and share expertise across the organization • Support knowledge sharing, cross-training, and team resilience initiatives Technical Skills & Tools Required • Strong proficiency in Python and SQL • Experience developing and deploying production AI applications • Azure Databricks and cloud platforms such as Azure or AWS • Enterprise LLM platforms including Azure OpenAI, AWS Bedrock, or equivalent • Retrieval Augmented Generation (RAG) architectures and vector databases • REST APIs and modern integration practices • Software engineering best practices, testing, and CI/CD • Solution architecture and enterprise application integration experience Preferred • LangChain, LangGraph, Semantic Kernel, Strands Agent SDK, or similar frameworks • React, TypeScript, Plotly Dash, Streamlit, or related technologies • Salesforce, ServiceNow, SAP, or Microsoft 365 integration experience • Agent orchestration frameworks and multi-agent architectures • Experience delivering AI use cases at enterprise scale. Qualifications Required • Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical field. • 8+ years of experience in software engineering, machine learning engineering, AI platform engineering, or related disciplines. • Demonstrated experience designing, building, and operating enterprise AI/ML platforms. • Strong understanding of cloud-native architectures, MLOps, deployment automation, monitoring, and production operations. • Experience building reusable engineering frameworks, platform services, or shared infrastructure capabilities. • Strong communication, collaboration, and stakeholder management skills Preferred Experience • Master's degree in Computer Science, Engineering, AI/ML, or related field. • Experience delivering enterprise-scale AI/ML platforms supporting multiple business domains. • Experience operating in regulated or compliance-sensitive environments. • Experience scaling platform engineering capabilities supporting machine learning, generative AI, and agent-based systems Additional Information • Position 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 MBUSA's Data Insights & AI organization and contributes to the company's long-term AI strategy and operating model.