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This role is for one of our clients
We are looking for a high-ownership product leader who understands the realities of modern software delivery and has experienced firsthand the challenges of engineering quality, release visibility, testing inefficiencies, and scaling delivery velocity. This is a strategic role designed for someone who thrives at the intersection of product, engineering, quality, and platform thinking.
You will work directly with leadership to shape and scale an AI-powered enterprise quality intelligence platform that bridges the growing gap between rapid code generation and reliable software delivery. The role requires deep understanding of software engineering workflows, SDLC health, quality metrics, testing ecosystems, and developer productivity challenges.
This is not a conventional product management role focused only on coordination or feature tracking. It is meant for someone who thinks in systems, understands developer pain points deeply, and can transform technical complexity into scalable product outcomes. The ideal candidate is execution-driven, curious, technically grounded, and motivated by building category-defining products in fast-moving environments.
Job ID: 147634075
Skills:
technology products, roadmap strategy, feature delivery, product management, data driven insights
Skills:
product discovery , lean startup , Saas, Iot, cloud, Agile, Containers, IEC 61850, protection relays, Ai, fault recorders, Design Thinking, NPI methodologies, data-driven decision-making, DNP3, microservices architectures, Modbus, product management, electrical utilities, on-premise, ML tools, SCADA, smart grid device management
Skills:
User Research, Confluence, Agile Methodologies, Scrum, Jira, Data-driven decision-making, Aha, Kanban, Product management tools
Skills:
Statistical Analysis, Product Marketing, Data Analysis, program management, business development
Skills:
cloud communications , Apis, Product management, Video, Customer insights, Voice, 0?1 product development, Customer journeys, Messaging, Data experimentation
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