Principal AI ToolChain & Process Engineer

Organization-wide AI-Enabled R&D Strategy & Vision:

• Define and own the organization-wide AI-enabled R&D strategic vision, multi-year roadmap, and technology investment priorities, ensuring alignment with Mercedes-Benz global R&D objectives and business strategy.
• Present strategic recommendations to executive leadership (VP/CTO level) and drive cross-departmental consensus on AI adoption priorities and resource allocation.
• Establish governance frameworks for AI tool selection, evaluation, and deployment across the organization.

Enterprise AI Toolchain Architecture & Platform:

• Architect and oversee the enterprise-level AI-powered R&D toolchain ecosystem, defining technical standards, integration patterns, and platform capabilities (e.g., AI programming assistants, intelligent test generation, AI-assisted requirements analysis, AI Agent-based project management, multi-agent collaborative development platforms).
• Make critical technology selection and architectural decisions, balancing innovation with enterprise requirements (security, scalability, compliance, cost).
• Drive build-vs-buy decisions and vendor/partner evaluation for AI toolchain components.

Intelligent R&D Process Transformation:

• Lead organization-wide analysis and transformation of software development processes (requirements, design, coding, testing, release), identifying systemic bottlenecks and designing AI-powered solutions (predictive models, NLP, code generation, multi-agent systems) to fundamentally reshape working paradigms.
• Define and champion new AI-integrated development methodologies and process standards that become organizational best practices.

R&D Efficiency Measurement & Strategic Insights:

• Architect and own the organization-wide data-driven R&D efficiency measurement framework, defining key metrics (delivery cycle time, defect density, code reuse rate, AI tool adoption rate, developer productivity index), building AI-powered analytics platforms, and providing executive-level strategic insights and visual reports to drive data-informed investment decisions.

Technology Thought Leadership & Talent Development:

• Serve as the organization's technical thought leader in AI for software engineering, establishing the AI-driven R&D culture across departments, designing comprehensive training curricula, mentoring senior engineers and technical leads, and building an elite engineering organization capable of leveraging AI at scale.
• Represent Mercedes-Benz R&D at industry conferences, technical forums, and academic partnerships to establish external thought leadership and attract top talent.

Technology Foresight, Research & Innovation:

• Lead the continuous evaluation and strategic assessment of emerging AI technologies in software engineering (LLM, AI Agent, AI4SE, autonomous coding systems), conducting advanced technical pre-research, prototype validation, and feasibility studies. Define the innovation pipeline and explore breakthrough application scenarios for automotive software development.

Tech Committee Leadership & Cross-functional Governance:

• Lead and steer RDC Tech Committee activities, setting the technical agenda, driving architectural decisions, and ensuring alignment across teams on technology direction and people development.
• Establish and facilitate cross-functional technical review boards, architecture governance councils, and innovation steering committees.
• Drive continuous improvement of engineering practices, methodologies, and quality standards across the organization.
  
  
   

Required Experience:

• 12+ years of experience in software development, architecture, or R&D efficiency platform-related roles, with deep expertise in ASPICE deployment in automotive projects. At least 5 years in a senior/lead technical role with demonstrated organizational-level impact.
• Proven track record of defining and executing AI-driven transformation strategies at scale across multiple teams or departments, with quantifiable results (e.g., leading enterprise-wide AI programming assistant adoption, establishing intelligent testing frameworks, building organization-wide automated code review pipelines, AI-assisted requirements management systems, and AI Agent-based workflow automation).
• Demonstrated experience in establishing technical standards, best practices, and architectural guidelines that have been adopted across an organization.
• Experience mentoring and developing senior engineers and technical leads, with a track record of growing technical talent.

Technical Skills:

AI/ML Capabilities:

• Expert-level understanding of machine learning/deep learning principles, with extensive hands-on experience and thought leadership in Prompt Engineering, AI Agent frameworks (e.g., LangChain, AutoGen, CrewAI), vibe coding, harness engineering, context engineering, RAG systems, and multi-agent orchestration.
• Deep expertise in multiple mainstream large language models (e.g., GPT series, Claude, CodeLlama, DeepSeek) including API integration, fine-tuning, RLHF, model evaluation, and enterprise-grade private deployment strategies.
• Proven ability to architect end-to-end AI solutions from proof-of-concept to production deployment at enterprise scale, including AI Agent application platforms and intelligent workflow systems.
• Experience in building and scaling AI/ML platforms and infrastructure to support organization-wide adoption.

R&D Processes and DevOps:

• Expert-level understanding of modern software development processes and industry standards including ASPICE, Agile at Scale (SAFe), DevOps, CI/CD, and platform engineering. Ability to define and evolve organizational R&D process standards integrating AI capabilities.

Data Skills:

Strategic data-driven mindset with the ability to define organization-wide R&D efficiency measurement frameworks, architect data pipelines, design executive-level dashboards, and lead data-informed decision-making using advanced analytics platforms (e.g., SQL, Python, Tableau, Power BI) and AI-powered insights.

Soft Skills:

• Exceptional communication and stakeholder management skills, with the ability to influence executive leadership and drive consensus across multiple departments and global teams (development, testing, architecture, project management, product management).
• Visionary technical leadership with strong strategic thinking, the ability to translate business objectives into technical initiatives, and a passion for pioneering new approaches to complex engineering challenges.
• Proven ability to build high-performing technical teams and foster an innovation-driven engineering culture.

Preferred Qualifications:

• Experience as a principal/staff engineer or technical director leading enterprise-wide R&D efficiency platform construction or major digital transformation programs at large technology companies, internet companies, or smart device (mobile/automotive) manufacturers.
• Deep familiarity with automotive software development standards and characteristics (e.g., ASPICE, Functional Safety ISO 26262, AUTOSAR, SOTIF) and experience integrating AI solutions within safety-critical development environments.
• Published thought leadership (papers, patents, conference talks) in AI for software engineering or related domains.
• Master's degree or PhD in Computer Science, Artificial Intelligence, Software Engineering, or a related field.