Product Manager- AI Data Center Power Platforms at SolarEdge

Modi'in Illit, Judea and Samaria, Palestinian Territory -

Full Time

Start Date

Immediate

Expiry Date

09 May, 26

Salary

0.0

Posted On

08 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Product Management, Power Electronics, Energy Systems, Infrastructure, Technical Program Management, Customer Technical Alignment, Validation Strategy, Architecture Tradeoffs, End-to-End Execution, Software-Defined Systems, Solid-State Transformers, High-Voltage DC, Hyperscale Customers, Test Strategy, Reliability Evidence, Power Delivery

Industry

Renewable Energy Semiconductor Manufacturing

Description

The Mission: Solve the Power Density Crisis AI data centers are no longer constrained by compute alone - they are constrained by the physics of power delivery. SolarEdge is building next-generation power platforms for the AI era, moving beyond legacy copper-and-iron infrastructure toward software-defined power systems. Our architecture combines Solid-State Transformers (SST), High-Voltage DC (HVDC), and battery-backed buffering to unlock higher density, higher efficiency, and faster deployment for hyperscale customers. We are looking for a deeply technical Product Manager who operates at the intersection of hardware physics and software intelligence, translating customer requirements into validated engineering reality. What you will own System-Level Product Definition: Define the end-to-end architecture for AI data center power platforms, including SST/HVDC topology, protection coordination, and software-defined operating modes. Engineering-Grade Requirements: Own the PRD and turn customer needs into crisp, testable specs across HW/FW/SW, from MVP to scale. Positioning and Packaging: Define differentiation, product boundaries, integration strategy, and a roadmap aligned to real customer adoption. Key Responsibilities Drive Architecture Tradeoffs: Make data-driven decisions across constraints: efficiency vs safety vs footprint vs cost-to-deploy. Evidence and Validation Strategy: Define the “proof of trust” and orchestrate validation (fault injection, characterization, reliability evidence) required for hyperscaler-grade diligence. End-to-End Execution Leadership: Act as the execution leader for the product, driving delivery from requirements through prototype bring-up and customer pilots across RnD, Ops, QA, and service. Customer Technical Alignment: Build the artifacts that win technical confidence: technical briefs, pilot success criteria, and traceability matrices. Requirements 7+ years delivering complex mission-critical hardware + software products (PM, systems, technical program, or equivalent). Strong technical foundation in power electronics / energy systems / infrastructure, including how systems fail, recover, and get serviced. Proven ability to lead customer-facing technical work with demanding buyers (hyperscalers, neoclouds, critical infrastructure, EPCs). Preferred qualifications Direct experience with data center power (UPS, switchgear, busway, PDU, power quality, rack power). Familiarity with HVDC / 800 V DC architectures, protection strategies, and system-level power conversion chains. Experience turning validation into trust: test plans, characterization, evidence packs, and reliability readiness. Background in test strategy: turning “it works in the lab” into “it works in the field.” What we offer First-principles innovation: Build the power foundation of the AI era from the ground up, not incremental improvements to legacy tech. High-visibility impact: Work directly with senior leadership to shape the strategy for a major new business segment. The "Rare" Platform: The agility of a deep-tech startup backed by the manufacturing scale and bankability of a global market leader. Position email null

Responsibilities

The Product Manager will define the end-to-end architecture for AI data center power platforms and drive delivery from requirements through prototype bring-up and customer pilots. They will also make data-driven decisions regarding architecture tradeoffs and define the validation strategy for the product.