Software Development Manager, Billing Automation

The Position:

Veracyte is seeking an experienced Software Development Manager to lead the engineering team responsible for our AI-powered Billing Automation platform. This team builds and operates software that improves laboratory billing, reimbursement, claims processing, and other revenue-cycle workflows through cloud-native applications, enterprise integrations, workflow automation, and artificial intelligence. 

The Software Development Manager will be accountable for the team’s people leadership, technical direction, execution, and operational performance. This leader will establish effective engineering practices, develop a high-performing team, and ensure the predictable delivery of secure, reliable, and maintainable software. 

You will partner closely with Product Management, Revenue Cycle Management, Finance, Laboratory Operations, Data & AI, Enterprise Applications, Architecture, and CloudOps. Together, these groups identify business needs and deliver software that reduces manual effort, improves billing accuracy, accelerates reimbursement, and increases operational efficiency. 

The ideal candidate is, first and foremost, an accomplished software engineering manager with a strong record of developing engineers and delivering complex enterprise software. Experience with healthcare billing, revenue-cycle management, or AI-enabled products is valuable but not required. 

This is a hybrid role based out of our San Diego, CA or South San Francisco, CA office. We may also be open to remote for the ideal candidate. 

Key Responsibilities:

• Lead, mentor, and grow a high-performing software engineering team responsible for Veracyte's AI-Powered Billing Automation platform.
• Define and execute the engineering roadmap in partnership with Product Management, Revenue Cycle Management, Finance, Laboratory Operations, Data & AI, and Architecture.
• Deliver secure, scalable, and highly available cloud-native applications, APIs, and AI-enabled services supporting laboratory billing, reimbursement, claims processing, and revenue cycle workflows.
• Define the technical strategy for applying AI to billing automation, balancing innovation with reliability, security, regulatory compliance, and measurable business outcomes.
• Partner with AI engineers, data scientists, and business stakeholders to identify and prioritize opportunities for intelligent automation across the revenue cycle.
• Lead the development of AI-powered capabilities such as intelligent document processing, claims validation, exception handling, payer rule interpretation, coding assistance, workflow orchestration, and operational copilots.
• Design and implement integrations with enterprise platforms including ERP, CRM, laboratory information systems (LIS), electronic medical record (EMR/EHR) systems, clearinghouses, payer systems, and AI platforms.
• Establish engineering best practices for integrating generative AI and machine learning into production systems, including evaluation, monitoring, governance, observability, and human-in-the-loop workflows.
• Drive engineering excellence through modern software development practices including CI/CD, Infrastructure as Code (IaC), automated testing, code quality, security, and platform observability.
• Ensure applications meet performance, reliability, scalability, and compliance requirements while protecting sensitive healthcare and financial data.
• Collaborate with CloudOps and Platform Engineering to optimize AWS infrastructure for availability, performance, security, and cost efficiency.
• Establish engineering and operational KPIs that measure software quality, AI solution effectiveness, delivery predictability, and business impact.
• Foster a culture of ownership, experimentation, innovation, continuous learning, and responsible AI adoption.

Who You Are:

• Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 
• 6+ years of software engineering experience, including 3+ years managing software development teams. 
• Demonstrated success hiring, developing, and retaining high-performing engineers while managing performance, career growth, and team effectiveness. 
• Proven experience leading the design, delivery, and operation of enterprise software, including cloud-native applications, APIs, distributed systems, and systems integrations. 
• Strong knowledge of modern engineering practices, including architecture and design, automated testing, CI/CD, Infrastructure as Code, security, observability, and production support. 
• Experience managing the complete software development lifecycle while balancing feature delivery, software quality, technical debt, reliability, and long-term architectural needs. 
• Demonstrated ability to improve engineering execution, delivery predictability, and operational performance using iterative development practices and meaningful metrics. 
• Excellent communication, stakeholder-management, organizational, and problem-solving skills, with the ability to collaborate across technical and business teams. 

 

Preferred Qualifications:

• Experience delivering software for healthcare operations, revenue-cycle management, laboratory billing, claims processing, reimbursement, coding, or payer integrations. 
• Experience delivering AI-enabled products, intelligent automation, document processing, operational copilots, or workflow-orchestration solutions in production. 
• Familiarity with generative AI and machine-learning technologies, including LLMs, retrieval-augmented generation, vector search, AI agents, model evaluation, and human-in-the-loop workflows. 
• Experience integrating AI services or frameworks such as Amazon Bedrock, OpenAI, Anthropic, Azure OpenAI, LangGraph, LangChain, Semantic Kernel, or similar technologies. 
• Familiarity with healthcare regulations, standards, and transactions such as HIPAA, HL7, FHIR, X12, CPT, and ICD-10. 
• Experience with laboratory systems and workflows or enterprise platforms such as SAP, Salesforce, Workday, Oracle, clearinghouses, and electronic health record systems. 
• Experience modernizing legacy applications, leading distributed or hybrid teams, or working in regulated healthcare, diagnostics, life sciences, or medical-device environments. 
• Relevant AWS certification, such as Solutions Architect, Developer, or DevOps Engineer. 

 

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