ROLE MISSIONOwn the roadmap for Smartech AI's platform layer - the analytics, models, and shared services (anomaly detection, prediction, contextualization) that turn real-time plant data into reusable capabilities. Deliver well-governed services that accelerate every operator- and operations-facing application across the portfolio.
KEY RESPONSIBILITIESPlatform Strategy & Roadmap- Own the roadmap for models, inference APIs, and shared services built on real-time plant data; prioritize capabilities that unlock application value.
Adoption & Enablement- Drive adoption through SDKs, documentation, and enablement; gather requirements from application teams and plant stakeholders.
Execution & Delivery- Lead delivery with ML and engineering in Agile/Scrum - owning the backlog, story writing, and sprint planning.
Responsible AI & Governance- Embed evaluation, monitoring, and model governance for plant-critical use; ensure data privacy and compliance.
KEY PERFORMANCE INDICATORSAdoption- Apps / teams using services
- API & SDK usage
Performance- Service uptime / latency (SLOs)
- Model accuracy on plant data
Delivery- Sprint commitments met
- Concept-to-GA time
REQUIRED EXPERIENCE & QUALIFICATIONSProduct Management: 5+ years in software product management / product ownership, including 2+ years owning a technical or platform product in an Agile/Scrum environment - backlog ownership, story writing, and sprint planning with engineering.
Industrial Software: 2+ years in industrial / manufacturing software - Industrial IoT, MES, SCADA / historian, or plant-operations SaaS - with a demonstrated understanding of real-time plant data and operator-facing systems.
Operations-Facing Delivery: Proven record shipping operator- or operations-facing applications - dashboards, alerting, visualization, or workflow tools built on live / streaming data.
KNOWLEDGE, SKILLS & ABILITIES- AI/ML Fluency: Model lifecycle, inference, and APIs on plant data.
- Platform PM: Ships developer- and application-facing services.
- Industrial Domain: Understands real-time plant data and use cases.
- Agile Ownership: Backlog, stories, and sprint planning with engineering.
- Responsible AI: Evaluation, monitoring, and model governance.
- Influence: Effective across engineering, data, and application teams.
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