Leader, Product Support

The role

The Support Team Leader will lead a regional support team and manage incident leadership. This role involves growing a high-performing team, owning incident management, and scaling a support organization through AI adoption.

What you will do

• Manage daily support operations including strategic resourcing and staffing
• Serve as a first-line contact for regional escalations
• Build team culture and identity through meetings and career growth conversations
• Partner with the Incident Center of Excellence to mature the incident process
• Build and run a sustainable off-hours coverage model
• Analyze incident and support metrics to inform staffing and process decisions
• Drive consistent adoption of AI tools across support workflows
• Collaborate with Build, Product, Technical Account Managers, Customer Success, and Professional Services
• Represent support at customer-facing events

Required qualifications

• 2+ years management experience
• 5+ years SaaS support or professional services, or demonstrated leadership with experience assigning ticket work and managing queues and resources
• Working knowledge of support and incident tooling and industry best practices
• Coaches with empathy and exercises judgment prioritizing issues
• Skilled in, or has strong aptitude for, customer-facing crisis communication
• Experience with Enterprise-grade support
• Genuine enthusiasm for using AI in support
• Strong communicator and customer advocate
• Excellent written and verbal skills across departments, remote teams, and external stakeholders
• Comfortable working independently, adapting quickly to new demands, and solving complex problems

Nice to have

• Bachelor's degree in a life sciences related field (biology, microbiology, genetics, biotechnology, neurology, etc.)
• Direct research or lab experience

Before you apply

• You'll complete a brief AI-focused exercise or discussion

About the company

Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows.