Product Manager, Automation

We are rebuilding biotech for the AI era.

When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done.

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. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma.

ROLE OVERVIEW 

We are seeking a visionary Product Manager to lead Benchling's automation and data orchestration platform, transforming how life sciences organizations connect instruments, automate workflows, and orchestrate complex data pipelines across their R&D operations. This role is fundamental to realizing Benchling's ambition to become the compute and automation engine for scientific data—enabling zero-touch automation, agentic AI-driven experimentation, and seamless integration across the scientific data lifecycle.

As the PM for Automation, you will own the product vision, roadmap, and execution for Benchling's Pipelines platform and the Automation Designer experience—the customer-facing workflow builder that enables scientists and automation engineers to design, configure, and deploy sophisticated data automation workflows with both low-code and no-code capabilities. You will drive the evolution of the automation platform that spans instrument connectivity, data processing, API integrations, and intelligent orchestration.

RESPONSIBILITIES 

• Define and drive the product vision and strategy for Benchling's automation and data orchestration platform, including Pipelines (backend platform) and Automation Designer (customer UX) capabilities.

• Enable automation that orchestrates end-to-end scientific workflows—from instrument and automated workcell data capture through analysis, Benchling actions, and cross-system integrations. 

• Work closely with engineering teams to prioritize, develop, and launch product features that align with the company' s goals and user needs.

• Collaborate with UX/UI designers to ensure the Automation Designer provides a flexible, intuitive interface that enables customers to create complex, multi-step data automation workflows through a visual, low-code/no-code environment.

• Foster a culture of innovation, encouraging team creativity and problem-solving to address the complex needs of our users.

• Conduct thorough market research and user feedback sessions to understand the needs and challenges faced by end users, translating these insights into product features.

• Define KPIs and success metrics for automation adoption, workflow reliability, and the product' s impact on enhancing scientific research and decision-making processes.

• Collaborate cross-functionally with Platform, Infrastructure, and Application teams to ensure automation capabilities are scalable, reliable, performant, and seamlessly integrated into the broader Benchling platform, delivering unified customer experiences that support enterprise workloads and complex requirements.

• Drive the strategic evolution toward agentic AI and DBTL (design-build-test-learn) workflows while partnering closely with AI & Analytics teams to embed intelligent automation, experiment optimization, and lab-in-the-loop learning into scientific workflow orchestration.

• Partner with customer-facing teams (Sales Consulting, Professional Services, Customer Success) to identify high-value automation use cases, build reference implementations, and drive adoption.

QUALIFICATIONS

• 5+ years of product management or relevant automation industry experience, preferably in B2B SaaS, with a focus on workflow automation and data orchestration platforms.

• Strong technical background, including deep understanding of APIs, data pipelines, ETL workflows, and software engineering principles.