Distribution Business Manager (Semiconductor Sales)

About the role

NXP is hiring a Distribution Business Manager (DBM) as a Global Sales Account Manager for its Semiconductor Intelligence Partners (SIPL) program. The role leads growth through distribution partners in a territory within the Central US (Austin TX, Novi MI, Chicago IL, or home-based, with the candidate living in the Central US). The DBM maintains close knowledge of major accounts and prioritizes territory growth in revenue, funnel development, design wins and customer expansion.

Key responsibilities

• Own and execute territory growth strategies aligned with NXP's Intelligent Edge vision, driving market share and customer expansion.
• Build partnerships with distribution leaders, running Quarterly Business Reviews (QBRs) with branch General Managers.
• Develop joint business plans with distribution partners, including demand creation, seminars and tailored engagement to accelerate design wins.
• Deliver a regular training cadence for distribution teams on NXP solutions, strengthening FAEs and FSRs.
• Run local and corporate marketing campaigns with partners and perform regular funnel reviews to keep the pipeline healthy.
• Join joint customer visits with distribution personnel and act as escalation point for technical and commercial issues.
• Drive internal alignment across NXP stakeholders so channel success is supported.

Required profile

• BS or MS in Electrical Engineering or a related field.
• Demonstrated track record of consistently meeting and exceeding sales quotas.
• At least 5 years of experience in semiconductor technical sales, distribution management or field applications engineering.
• Strong technical aptitude and ability to stay current with processing, connectivity and analog technologies.
• Willingness to travel primarily domestically.

Preferred skills

• At least 2 years of distribution management and QBR experience.
• Familiarity with CRM tools, funnel management and opportunity review best practices.
• Knowledge of embedded computing architectures (MCU, MPU, accelerators such as NPUs) and exposure to AI-enabled systems and Edge AI concepts.