Solutions Architect

Enterprise Architecture Ownership

• Serve as the design and architecture authority for AI solutions across Knorr-Bremse's global operations.
• Develop reference architectures and reusable solution templates that streamline the implementation of AI-driven workflows, ensuring scalability, performance, and ease of integration.
• Lead end-to-end AI solution delivery from concept to large-scale deployment, ensuring resilience, scalability, and compliance.

AI Foundation Layer Development

• Architect and implement a foundation layer for AI, integrating data, cloud, and application ecosystems.
• Establish enterprise-grade frameworks for MLOps, model governance, monitoring, retraining, and lifecycle management.
• Build reusable AI components, microservices, and accelerators that enable rapid and standardized adoption.
• Collaborate with engineering teams to ensure microservices and AI capabilities are production-ready, maintainable, and aligned with compliance standards such as, GDPR, and EU AI act and internal information and data security guidelines.
• Advocate for best practices in AI architecture, MLOps, data pipeline design, and observability across KB's ecosystem of solutions.
• Responsibility for assessing legacy AI systems for cloud migration and leading migration projects.

Adoption of Emerging AI Architectures

• Drive enterprise-wide adoption of agentic AI and emerging architectures, enabling intelligent, autonomous, and context-aware systems.
• Translate research into enterprise solutions, including predictive maintenance, IoT-driven insights, and digital factory use cases.
• Define processes and governance to continuously evaluate, pilot, and scale new AI technologies across the organization.

Collaboration & Stakeholder Engagement

• Partner with R&D, IT, engineering, and business stakeholders to align AI architectures with enterprise goals.
• Collaborate with technology partners (AWS, Microsoft, Google) and academic institutions to bring cutting-edge innovations into Knorr-Bremse.
• Establish and champion enterprise-wide AI adoption roadmaps and maturity models.

Leadership & Mentorship

• Lead and mentor AI architects, engineers, and scientists within the AI CoE.
• Promote a culture of innovation, architectural discipline, and knowledge sharing.
• Balance hands-on technical leadership with enterprise-scale strategic influence.

Skills:

• Cloud Platforms: Azure, GCP, AWS
• Containerization: Kubernetes, on-cloud/on-prem orchestration
• API Design & Development, Microservices Architecture
• Event-Driven Architecture, Domain-Driven Design (DDD)
• Data Virtualization, NoSQL & Relational Databases
• AI & Machine Learning concepts, Agentic Architecture
• Cloud-based AI services (e.g., Azure ML, AWS SageMaker, Google Vertex AI) and orchestration of AI workloads in cloud environments
• Optimizing cloud resource usage for AI workloads (e.g., autoscaling, cost monitoring, efficient use of GPU/TPU resources)

Delivery & Program Management

• Agile methodologies (Scrum, Kanban)
• Risk, Vendor & Stakeholder Management
• Large-scale Program & Project Leadership

Strategic Skills

• Enterprise Solution & Digital Transformation
• Strategic Planning & Execution
• Team Leadership & Mentoring
• Consulting & Advisory for innovation and emerging technologies

Experience:

• Experience: 15+ years of experience in solution architecture (IT) with 5+ years of experience in Data Science and AI/ML based solution architecture, applied AI/ML with proven impact in industrial, mobility, or large-scale enterprise settings.
• Track record of design and scaling impactful enterprise IT application
• Experience in IoT and designing technical architecture for digital innovations
• Strong team leadership and mentoring experience.
• Entrepreneurial, innovative, and execution-focused mindset.

Education:

• Education: B.Tech/ Master's in IT,, Computer Science, Engineering or related fields
• Certification in Cloud professional