Company Description

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. 

Key Responsibilities:

Data Engineering & Pipeline Development

• Design, build, and maintain large-scale ETL/ELT pipelines using AWS Glue and related AWS services.

• Develop and optimize data models across Amazon S3, Redshift, and Neptune to support analytics and AI workloads.

• Implement transformation and data modeling workflows, ensuring data accuracy, consistency, and lineage.

• Manage data orchestration using Apache Airflow or AWS Step Functions to ensure reliability and timely data delivery.

• Integrate data from CRM platforms, marketing systems, provider datasets, and operational tools into scalable commercial data pipelines.

Agentic AI Application Development

• Build Agentic AI-driven workflows using Agentic AI frameworks such as Langchain, Langgraph, Strands, LLMs and Knowledge Bases

• Develop multi-agent systems that support sales enablement, provider insights, and commercial operations automation.

• Implement retrieval-augmented generation (RAG) pipelines and hybrid search workflows using vector databases and AWS-native retrieval tools.

• Build and maintain Amazon Neptune knowledge graph.

• Integrate agent capabilities with internal systems and APIs to support use cases such as provider briefings, objection handling, triage workflows, and content generation.

• Implement security guardrails and access control for agent tools.

• Develop evaluation, telemetry, and monitoring processes to assess agent performance, detect hallucinations, and ensure workflow stability.

Cross-Functional Collaboration

• Work closely with Product teams, Commercial Operations, Sales and Marketing, Data Engineering, and to identify automation opportunities.

• Translate business requirements into scalable technical solutions with high reliability and security.

• Provide technical leadership and best practices for AI-driven workflow development

Qualifications:

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience.

• 5+ years of professional experience in data engineering, AI engineering, or related fields.

• Strong expertise with AWS data engineering technologies, including: AWS Glue, Amazon S3, Amazon Neptune/Redshift, Apache Airflow

• Hands-on experience with agentic AI frameworks such as:

• AWS Strands SDK and Bedrock (highly preferred)

• Strands SDK, LangGraph, LangChain, CrewAI, or AutoGen

• Strong proficiency in Python and experience with distributed data processing frameworks.

• Practical understanding of LLMs, embeddings, vector search, RAG pipelines, and multi-agent orchestration.

• Experience building secure, reliable workflow systems with attention to guardrails, error handling, and compliance.

Preferred Qualifications

• Experience integrating data from CRM systems (e.g., Salesforce) or other GTM platforms.

• Experience in commercial operations, sales enablement, healthcare analytics, or diagnostic products.

• Familiarity with healthcare data compliance, including HIPAA and PHI handling.

• Experience with Docker, CI/CD pipelines, Kubernetes, or observability tools (CloudWatch , Prometheus, Grafana).

Competencies

• Strong analytical and problem-solving skills.

• Ability to work independently in fast-paced, dynamic environments. AI-native builder quick prototype who iterates fast.

• First-principles thinker who chooses tools for correctness and efficiency.

• Excellent communication skills with the ability to collaborate across technical and non-technical teams.

• High attention to detail with a commitment to reliability, accuracy, and compliance.

• Mission-driven mindset focus.

Hybrid Work Model: This section is applicable to onsite employees who are eligible for hybrid work location as specified by management and related policies.  Guardant has defined days for in-person/onsite collaboration and work-from-home days for individual-focused time. All U.S. employees who live within 50 miles of a Guardant facility will be required to be onsite on Mondays, Tuesdays, and Thursdays. We have found aligning our scheduled in-office days allows our teams to do the best work and creates the focused thinking time our innovative work requires. At Guardant, our work model has created flexibility for better work-life balance while keeping teams connected to advance our science for our patients. 

The annualized base salary ranges for the primary location and any additional locations are listed below. This range does not include benefits or, if applicable, bonus, commission, or equity. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, education, job-related skills, job duties, and business need. Primary Location: Palo Alto, CA Primary Location Base Pay Range: $121,000 - $166,400 Other US Location(s) Base Pay Range: $102,850 - $141,440 If the role is performed in Colorado, the pay range for this job is: $108,900 - $149,760