Business Performance

Location: Anywhere in Country

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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

• 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 demonstrati