招聘
Biotechnology is rewriting life as we know it, from the medicines we take, to the crops we grow, the materials we wear, and the household goods that we rely on every day. But moving at the new speed of science requires better technology.
Benchling’s mission is to unlock the power of biotechnology. The world’s most innovative biotech companies use Benchling’s R&D Cloud to power the development of breakthrough products and accelerate time to milestone and market.
Come help us bring modern software to modern science.
ROLE OVERVIEW:
The Product Support Leader will lead our West Coast customer support team in close collaboration with our Global Support Leadership Team and Customer Experience Leadership Team. This is a hands-on leadership role responsible for delivering excellent technical support to Benchling's customers — including a growing portfolio of enterprise pharmaceutical companies operating in regulated, GxP environments — while developing a high-performing team and contributing to the evolution of our global support strategy.
This role comes at a defining moment. Benchling is rapidly scaling its enterprise customer base and expanding into AI-powered capabilities that are changing how scientists interact with our platform. The Support team needs to evolve alongside those shifts — building enterprise-grade support practices, developing new expertise around AI product features, and deepening the trust that our largest customers place in us every day. You'll help lead that transformation.
We're looking for someone who combines strong people leadership with deep customer empathy: a leader who can represent Support credibly in front of customers, account teams, and cross-functional partners, and who brings a point of view on how to continuously improve how we serve our customers.
RESPONSIBILITIES:
TEAM LEADERSHIP & DEVELOPMENT:
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Develop, coach, and grow a team of support professionals — setting clear expectations, providing regular feedback, managing performance, and investing in career development aligned with Benchling's "Recruit and develop the best" principle
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Build team capabilities to support Benchling's expanding product surface, including AI agents, predictive models, and new automation features that are rapidly becoming part of scientists' daily workflows
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Ensure the team continuously documents and updates product knowledge in help articles and internal knowledge bases, including emerging AI product capabilities
Operations & Service Delivery:
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Own the daily operations of West Coast customer support, including strategic resourcing, queue management, and capacity planning to deliver consistent, high-quality service across all customer segments
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Own and report on support metrics and KPIs (volume, case trending, resolution time, CSAT), using data to drive decisions and building influence through voice-of-customer insights shared with Product, Engineering, and CX leadership
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Lead and drive process improvement initiatives with measurable outcomes — identifying gaps, proposing solutions, and executing changes that elevate the customer support experience
Customer & Stakeholder Engagement:
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Serve as the primary escalation point for West Coast customers, deeply understanding scientist pain points and ensuring timely, high-quality resolution in partnership with Engineering, Product, and CX teams
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Collaborate cross-functionally with Customer Success, Professional Services, Account Management, Product, Engineering, and delivery partners (including Zifo) to coordinate on customer issues through resolution
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Partner with the Head of Support to shape and execute the support strategy, contributing insights on process improvement, tooling, team structure, and enterprise readiness
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Represent Support in customer visits, meetings, conferences, QBRs, and marketing events as a credible, customer-facing leader
QUALIFICATIONS:
Required
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5+ years of experience in technical customer support, professional services, or a related customer-facing role in B2B software, ideally SaaS
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2+ years of people management experience, with a demonstrated track record of building, coaching, and developing high-performing support teams
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Proven ability to manage customer escalations with composure, empathy, and a bias toward resolution — including experience representing your organization in live customer conversations
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Strong operational skills: experience managing ticket queues, resourcing, prioritization frameworks, and SLA-driven environments using tools like Salesforce, Zendesk, JIRA, or similar platforms
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Excellent judgment in prioritizing customer issues based on urgency, severity, and business context (e.g., customer health, contract value, renewal timing)
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Strong written and verbal communication skills — able to communicate clearly and credibly across functions, levels, and geographies, including with customers, account teams, and engineering partners
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Experience with cross-functional collaboration in a post-sales environment, including working with Customer Success, Professional Services, and Engineering teams
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Demonstrated ability to analyze complex problems, identify root causes, and drive systemic improvements
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Flexible, action-oriented, and comfortable operating independently in a fast-paced, evolving environment
Preferred
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Bachelor's degree in a life sciences field (biology, microbiology, genetics, biotechnology, etc.) — direct research or lab experience is a significant plus
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Experience supporting enterprise customers, particularly in regulated industries (pharma, biotech, GxP environments) where platform reliability and compliance have direct business and patient-safety implications
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Experience supporting products through major capability expansions, such as AI/ML feature launches or platform shifts that require building new team expertise rapidly
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Experience working with outsourced or partner-delivered support teams
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Familiarity with knowledge management practices and help center content strategy
HOW WE WORK:
We offer a flexible hybrid work arrangement that prioritizes in-office collaboration. Employees are expected to be on-site 3 days per week (Monday, Tuesday, and Thursday).
#BI-Hybrid
Benchling welcomes everyone.
We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.
We are an equal opportunity employer. That means we don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.
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关于Benchling

Benchling
Series F+Benchling provides a cloud-based platform for life sciences research and development, offering tools for data management, laboratory workflows, and bioinformatics. The company serves biotechnology and pharmaceutical organizations to accelerate their R&D processes.
501-1,000
员工数
San Francisco
总部位置
$6.1B
企业估值
薪资范围
51个数据点
Junior/L3
Mid/L4
Junior/L3 · Product Support Analyst
1份报告
$97,175
年薪总额
基本工资
$84,500
股票
-
奖金
-
$97,175
$97,175
新闻动态
Benchling Launches AI Connectors to Deepen Integration Between R&D Data and Enterprise AI Tools - TipRanks
TipRanks
News
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1w ago
Benchling Launches AI Connectors to Power the Data Ecosystem for R&D - PR Newswire
PR Newswire
News
·
1w ago
[1 YoE, Application Scientist, Field Application Scientist, France]
Hello everyone, I need some feedback for my resume, I'm a PhD in mol/cell biology (3years) with a first exeprience as application scientist (fixed term contract, unfortunately, due to budget restriction and logistic issues they couldn't keep me) I want to find a similar job or a field application scientist (so visiting customers, training them, troubleshooting their protocols etc..), but so far no luck. I have been networking a ton, with lots of FAS telling me they got their first FAS job right
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4w ago
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6
Does Benchling actually generate real value, or is it just overhead?
I’ve been using Benchling in an industry R&D setting, and I’m trying to figure out whether it’s genuinely high ROI or just something teams feel obligated to use. In theory, it should act as a central system for experiment tracking, data organization, and collaboration. But in practice, I’ve seen a few issues: * A lot of manual data entry with unclear downstream use * Data stored but rarely reused or queried * Limited integration with analysis pipelines (R/Python) * Scientists treating it a
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4w ago
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2