Location:

Anywhere in Country At EY, we're all in to shape your future with confidence. We'll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. The opportunity As a Solution Senior Manager in Supply Chain Manufacturing Operations, you will lead the design, build, testing, and scaling of differentiated AI-enabled manufacturing solutions. You will combine deep manufacturing and supply chain domain knowledge with manufacturing data platforms, industrial data architectures, predictive and generative AI, knowledge graphs, retrieval-augmented generation ( RAG ), data ontologies, and reusable application components This is a senior, hands-on solution leadership role. The primary purpose of the position is to set direction and lead teams that create working solutions, prototypes, accelerators, demonstrations, reference architectures, and reusable intellectual property that can be configured and deployed by pursuit and delivery teams. You will lead and collaborate with manufacturing practitioners, Managers, data engineers, data scientists, AI engineers, software developers, architects, alliance teams, and solution leaders to turn priority manufacturing use cases into production-oriented solution assets. You will be accountable for solution strategy, technical credibility, quality and risk management, commercial relevance, talent development, repeatability, and adoption across the practice. Your key responsibilities As a Solution Senior Manager in Supply Chain Manufacturing Operations, you will be responsible for the strategy, portfolio direction, and end-to-end development of AI-enabled manufacturing solutions and the reusable data and technology foundations required to scale them across pursuits and engagements.

+ Set the vision, roadmap, investment priorities, and quality standards for a portfolio of AI-enabled manufacturing solutions, prototypes, accelerators, demonstrations, and reusable solution components.

+ Lead Managers and multidisciplinary teams through concept definition, architecture, build, testing, release, adoption, and continuous improvement while remaining sufficiently hands-on to challenge technical decisions and resolve critical issues.

+ Translate manufacturing and supply chain priorities into compelling AI use cases, value hypotheses, user stories, functional and technical requirements, data and model requirements, acceptance criteria, and measurable operational outcomes.

+ Own solution governance, including architecture decisions, responsible AI, cybersecurity, data privacy, quality, risk, release readiness, documentation, and compliance with firm development standards.

+ Direct the design of manufacturing data platforms that connect and contextualize data from

MES / MOM , ERP

, historians, SCADA , PLC , IoT, quality, maintenance, laboratory, warehouse, engineering, document, image, and enterprise systems.

+ Guide the development of reusable manufacturing data models, ontologies, semantic layers, taxonomies, metadata, entity relationships, knowledge graphs, and governance standards spanning assets, products, materials, production, quality, maintenance, inventory, energy, labor, and performance.

+ Lead the design and industrialization of RAG and GraphRAG solutions using governed manufacturing content, operational data, embeddings, vector search, knowledge graphs, metadata filtering, evaluation methods, guardrails, and human oversight.

+ Shape AI assistants, copilots, agents, predictive models, and intelligent workflows for use cases such as predictive maintenance, anomaly detection, root-cause analysis, quality investigation, production optimization, shift handover, troubleshooting, energy optimization, and operational decision support.

+ Lead the configuration and extension of SymphonyAI industrial capabilities and comparable industrial data and AI platforms, including data foundations, unified namespace patterns, knowledge graphs, industrial AI models, copilots, agent workflows, and low-code or no-code applications.

+ Oversee integrations and reusable connectors using APIs, event streams, industrial protocols, data pipelines, orchestration tools, and common IT/OT integration patterns.

+ Establish engineering standards for reusable code, source control, configuration management, model versioning, data quality, testing, DevOps, DataOps, MLOps, LLMOps, security, release management, and solution documentation.

+ Own solution backlogs and product roadmaps; prioritize features, define releases, manage technical dependencies, allocate resources, and coordinate contributors through agile development cycles.

+ Partner with senior practice, account, pursuit, alliance, and delivery leaders to identify market needs, shape differentiated offerings, estimate effort and investment, support proposals and demonstrations, and enable successful adoption.

+ Support technical sales and business development by leading solution discovery and technical qualification, shaping architectures and implementation approaches, developing compelling demonstrations and proofs of concept, contributing to proposals, statements of work, estimates, pricing inputs, and oral presentations, and articulating the differentiated value, feasibility, scalability, and risk profile of proposed manufacturing solutions to client and internal stakeholders.

+ Contribute to revenue generation by identifying opportunities, shaping the solution and value proposition, supporting proposal development and pricing, and building trusted relationships with internal and selective client stakeholders.

+ Manage solution-development budgets, staffing, milestones, risks, dependencies, and investment decisions; communicate progress, outcomes, and escalation needs to senior stakeholders.

+ Package solutions for reuse through reference implementations, technical documentation, configuration guides, architecture diagrams, data-model specifications, test assets, deployment guidance, and enablement materials.

+ Serve as a senior solution expert for pursuits and delivery teams while remaining primarily accountable for internal solution engineering rather than ongoing engagement delivery.

+ Lead, coach, and develop Managers, engineers, analysts, and specialists; provide timely feedback, support career development, strengthen inclusive teaming, and build the next generation of manufacturing solution leaders. Skills and attributes for success To excel in this role, you will need a builder mindset, senior leadership presence, and the ability to move from an ambiguous manufacturing problem to a technically credible, commercially relevant, reusable solution while directing teams and influencing stakeholders.

+ Deep manufacturing and supply chain credibility with the ability to connect operating model, process, data, technology, workforce, and business-value considerations.

+ Senior-level solution-engineering leadership across manufacturing operations, industrial data, AI, applications, integration, cybersecurity, and deployment.

+ Strong understanding of manufacturing data platforms, industrial DataOps, unified namespaces, data fabrics, data products, contextualization, semantic modeling, ontologies, knowledge graphs, and edge-to-cloud architectures.

+ Practical experience directing RAG or GraphRAG solutions, including ingestion, chunking, embeddings, vector and graph retrieval, reranking, grounding, prompting, evaluation, observability, and responsible AI controls.

+ Strong data-modeling and architecture skills across conceptual, logical, physical, semantic, time-series, event, graph, and application models, including alignment with

ISA -95, ISA

-88, asset hierarchies, and manufacturing process models. + Ability to evaluate predictive, prescriptive, generative, and agentic AI opportunities To view full details and how to apply, please login or create a Job Seeker account