Principal Engineer - Supply Chain and Manufacturing

Location: Bengaluru

Job Description Summary

Principal Engineer - Supply Chain and Manufacturing leads the technical design, architecture, and delivery of our Supply Chain and Manufacturing solutions across our global industrial operations. This role is the technical backbone of our manufacturing digitalization and supply chain optimization strategy, ensuring our production systems, OT/IT convergence, and supply chain platforms are engineered for scalability, reliability, and innovation.
The Principal Engineer will drive technical excellence across ERP, MES, Supply Chain planning, automation, and integration layers to support world-class manufacturing and supply chain performance for the Wind segment in GE Vernova.

Job Description

ESSENTIAL RESPONSIBILITIES

• Define and own the technical architecture, standards, and engineering roadmap for Supply Chain and Manufacturing systems, ensuring alignment with enterprise IT strategy and operational objectives.
• Lead the design, development, and implementation of manufacturing and supply chain solutions including ERP (Oracle EBS), MES, Integrated Business Planning, OT systems, robotics integration, and material flow and warehouse management platforms.
• Architect and oversee integration patterns and data flows across manufacturing and supply chain systems, leveraging Boomi middleware to ensure seamless connectivity and data integrity across the enterprise landscape.
• Partner with manufacturing, supply chain, ERP, and operational technology teams to translate complex business requirements into scalable, robust technical solutions.
• Support the Manufacturing Robotization & OT modernization program from a technical perspective, ensuring IT/OT convergence, cybersecurity, and industrial IoT best practices are embedded in solution design.
• Establish and enforce engineering best practices, code quality standards, and technical governance across the supply chain and manufacturing technology portfolio.
• Lead technical evaluation, selection, and integration of new technologies including AI/ML, digital twins, advanced analytics, and edge computing to continuously improve manufacturing and supply chain outcomes.
• Operationalize engineering processes to ensure continuous adaptation and improvement of solutions to maximize business value and manufacturing performance.
• Drive an innovation culture through application of automation and AI to improve production efficiency, quality, and supply chain responsiveness.

QUALIFICATIONS / REQUIREMENTS

• Extensive engineering experience with ERP systems (Oracle EBS preferred), MES platforms, Supply Chain Planning, and industrial automation technologies in global manufacturing environments.
• Deep technical expertise in supply chain and manufacturing processes including production planning, shop floor execution, quality management, inventory control, and logistics.
• Proven experience designing and delivering large-scale integration architectures using middleware platforms in complex, multi-site industrial organizations.
• Strong understanding of OT/IT convergence, industrial IoT, SCADA systems, and manufacturing robotics — with direct experience in Manufacturing Robotization & OT programs.
• Hands-on experience with implementing (gen)AI solutions at scale
• Demonstrated ability to drive technical decisions in a global, matrixed organization.
• Excellent technical communication skills with the ability to articulate complex engineering concepts clearly to both technical and business stakeholders.

DESIRED CHARACTERISTICS

• High energy, self-motivated, and passionate about manufacturing technology innovation and operational excellence.
• Strong quantitative, analytical, and problem resolution skills with a hands-on engineering mindset — comfortable working at both architectural and implementation levels.
• Lean understanding and mindset with experience applying continuous improvement principles to technology delivery and manufacturing operations.
• Curiosity and drive to explore emerging technologies (AI, digital twins, edge computing) and apply them pragmatically to industrial challenges.
• Collaborative, able to build strong relationships across engineering, operations, and business functions in a global, diverse organization.

Additional Information