Principal SME - Manufacturing Engineering & Digital

Job Description Summary

The SME will act as a customer-facing advisor and internal capability leader, translating manufacturing challenges into actionable transformation roadmaps, proposal opportunities, and delivery programs. The role requires a strong combination of manufacturing engineering depth, digital technology awareness, project/program execution discipline, and consultative customer engagement.

Key Responsibilities

1. Customer Engagement & Business Growth

• Engage with manufacturing, industrialization, quality, operations, and engineering stakeholders to understand priorities, pain points, and future roadmap needs.
• Identify white-space opportunities across manufacturing engineering, inspection modernization, tooling, process planning, automation, analytics, and digital transformation.
• Develop customer-ready proposals, solution narratives, business cases, effort estimates, delivery assumptions, and implementation roadmaps.
• Facilitate discovery workshops, maturity assessments, technology demonstrations, and executive reviews.
• Partner with account, delivery, and solution teams to convert ideas into a qualified pipeline and executable programs.

2. Manufacturing Engineering & Technology Leadership

• Provide domain leadership in aerospace manufacturing engineering, including process planning, industrialization, work instructions, producibility, manufacturing validation, tooling, fixture design, and assembly methods.
• Lead solution development in Model-Based Definition, Model-Based Manufacturing Information, digital manufacturing, and digital thread enablement.
• Drive opportunities around robotic inspection, automated dimensional inspection, machine vision, CMM automation, NDI/NDT data workflows, and AI-enabled defect detection.
• Evaluate smart factory technologies, including MES integration, Industrial IoT, real-time shop-floor dashboards, OEE improvement, predictive quality, and manufacturing intelligence.
• Build point-of-view assets, reference architectures, accelerators, playbooks, reusable templates, and technology roadmaps.

3. Program Delivery & Roadmap Execution

• Translate customer roadmap themes into structured execution plans with scope, milestones, dependencies, risks, benefits, and governance cadence.
• Apply project management, Agile, and Scrum practices to improve delivery predictability, stakeholder alignment, backlog visibility, and value realization.
• Support program governance through steering reviews, sprint or milestone planning, risk registers, RAID logs, and benefit tracking.
• Ensure solution proposals are delivery-ready with clear assumptions, resource models, transition approaches, KPIs, acceptance criteria, and change management considerations.
• Collaborate with delivery managers to ensure proposed solutions are scalable, commercially viable, and aligned to Cyient delivery capabilities.

4. Capability Building & Team Enablement

• Mentor manufacturing engineering teams on domain practices, digital manufacturing trends, customer context, and consulting-led delivery approaches.
• Define competency roadmaps, skill matrices, and training plans for MBD/MBMI, inspection automation, manufacturing analytics, and Industry 4.0.
• Support hiring, interviews, technical assessments, and creation of a Manufacturing Engineering SME community within the P&WC CoE.
• Establish partnerships with technology providers, universities, or internal digital teams where needed to build differentiated offerings.

Strategic Focus Areas

Focus Area

Opportunity Themes

Model-Based Enterprise

MBD, MBMI, model-centric manufacturing, 2D-to-3D transformation, model-based work instructions, digital thread.

Inspection Modernization

Robotic inspection, automated inspection planning, AI-enabled visual inspection, CMM automation, metrology data management.

Manufacturing Execution & Analytics

MES workflows connected shop-floor data, Power BI dashboards, OEE analysis, production monitoring, and predictive quality.

Industrialization & NPI

Manufacturing readiness assessments, process planning, manufacturability reviews, tooling/fixture digitization, assembly optimization.

AI & Automation

AI/ML use cases for defect prediction, process recommendations, knowledge management, intelligent routing, and decision support.