Guardant Health-posted 20 days ago
Full-time • Mid Level
Hybrid • Palo Alto, CA
1,001-5,000 employees

Guardant Health is a leading precision oncology company focused on guarding wellness and giving every person more time free from cancer. Founded in 2012, Guardant is transforming patient care and accelerating new cancer therapies by providing critical insights into what drives disease through its advanced blood and tissue tests, real-world data and AI analytics. Guardant tests help improve outcomes across all stages of care, including screening to find cancer early, monitoring for recurrence in early-stage cancer, and treatment selection for patients with advanced cancer. For more information, visit guardanthealth.com and follow the company on LinkedIn, X (Twitter) and Facebook. Overview We are seeking an exceptional Product Manager with expertise in automation and AI, for close collaboration with internal teams and customers, to deliver comprehensive intelligent automation and agentic solutions. The ideal AI & Automation Solutions Product Manager (AASPM) is a strategic thinker with a strong engineering acumen—someone who excels at process mapping, rapid prototyping, and deploying reliable systems that drive measurable improvements. As an integral member of our Oncology Digital Product team, you will contribute to product strategy and technology implementation across our digital portfolio, which includes both clinician-facing solutions and internal platforms supporting precision oncology operations. Our AASPM is a systems thinker who thrives in customer-facing environments, and is eager to work hands-on with modern AI technologies. Proficiency with leading AI and automation tools—such as Microsoft Copilot, ServiceNow, UiPath/Power Automate, Slack/Zoom bots, and Zapier/Make—is essential. You will rigorously assess business impact, champion process transformation, and empower operational subject matter experts to become self-sufficient “user-builders,” enabling them to manage key business levers effectively.

  • Embed with customer and internal teams to map current/target processes, identify automation/AI opportunities, and define success metrics and ROI.
  • Lead structured discovery (interviews, shadowing, data/queue analysis), translate needs into clear problem statements, requirements, and backlogs.
  • Run iterative delivery using agile methods—prototype → pilot → production—and manage change, training, and adoption.
  • Design and build automated/agentic and workflow solutions across the stack: Salesforce, Lab systems, and in-house platforms.
  • Implement RPA/workflow automation where appropriate (Power Automate, UiPath, ServiceNow flows, Zapier), integrating with SFDC, data warehouses, and clinical/operational systems. Limit customization and maximize speed.
  • Create reusable patterns, templates, and components (prompts, tools, connectors) and maintain a catalog of approved solutions.
  • Define evaluation frameworks (quality, time savings, increased throughput), telemetry, and dashboards; instrument experiments (A/B, champion/challenger).
  • Partner with product/engineering on roadmaps; document architectures, runbooks, and handoffs for long‑term ownership.
  • Typically requires a university degree and generally 8 years of related experience; 6 years and a Master’s degree; 3 years and a PhD; or PharmD/MD.
  • 4+ years total experience across software engineering, business/process analysis/consulting, or product, with 3+ years focused on automation and/or applied AI.
  • Demonstrated success embedding with customers and shipping production solutions that improved measurable business outcomes.
  • Hands‑on proficiency with AWS, Salesforce, or RPA/workflow platform (Power Automate, UiPath, ServiceNow, or equivalent).
  • Practical experience building LLM‑powered applications: prompt design, tool/function calling, no-code building
  • Strong systems and process design skills (e.g., BPMN, swim lanes, value‑stream mapping) and data-informed communication.
  • Background in healthcare/regulated environments (HIPAA/PHI), or complex enterprise operations.
  • Familiarity with Salesforce Health Cloud/Einstein, contact center and case management patterns.
  • Experience with observability and analytics for automations (logging, tracing, dashboards) and LLM evaluation frameworks.
  • Exposure to MLOps and model lifecycle management; understanding of model and prompt risks.
  • Equally comfortable in stakeholder workshops and in code.
  • Clear, persuasive communicator who can teach, uplift, and bring teams along with them.
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