Manager Billing Automation

Veracyte•San Diego, CA

1d•$147,000 - $160,000•Hybrid

About The Position

At Veracyte, we offer exciting career opportunities for those interested in joining a pioneering team that is committed to transforming cancer care for patients across the globe. Working at Veracyte enables our employees to not only make a meaningful impact on the lives of patients, but to also learn and grow within a purpose driven environment. This is what we call the Veracyte way – it’s about how we work together, guided by our values, to give clinicians the insights they need to help patients make life-changing decisions. Veracyte is seeking an experienced Manager, Billing Automation, to lead our AI-Powered Billing Automation engineering team. This team is responsible for transforming our revenue cycle by building intelligent software solutions that automate laboratory billing, reimbursement, claims processing, and revenue cycle workflows. By combining cloud-native technologies, artificial intelligence, and workflow automation, the team delivers solutions that reduce manual effort, improve billing accuracy, accelerate reimbursement, and enhance operational efficiency. As the Manager, Billing Automation, you will provide technical leadership, people leadership, and strategic direction for a team developing scalable applications, APIs, AI-enabled services, and enterprise integrations. You will partner closely with Revenue Cycle Management, Finance, Product Management, Laboratory Operations, Data & AI, Enterprise Applications, Architecture, and CloudOps to identify opportunities where AI can streamline complex business processes and improve decision-making across the billing lifecycle. The ideal candidate is an experienced engineering leader who has successfully delivered enterprise software and AI-enabled solutions, enjoys building high-performing teams, and is passionate about leveraging emerging technologies to solve meaningful business challenges in a regulated healthcare environment. This is a hybrid role in San Diego, CA

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field.
6 – 7 years of software engineering experience, including 3+ years leading software engineering teams.
Proven success building and developing high-performing engineering teams delivering enterprise software solutions.
Experience designing and delivering cloud-native applications and distributed systems, preferably on AWS.
Experience delivering AI-enabled products or intelligent automation solutions in production environments.
Strong understanding of software architecture, APIs, systems integration, event-driven architectures, and modern software engineering practices.
Working knowledge of modern AI technologies including large language models (LLMs), retrieval-augmented generation (RAG), vector search, AI agents, prompt engineering, and orchestration frameworks.
Experience integrating AI platforms such as Amazon Bedrock, OpenAI, Anthropic, Azure OpenAI, or similar services into enterprise applications.
Experience leading Agile software development teams using iterative delivery methodologies.
Excellent communication and stakeholder management skills with the ability to collaborate across technical and business organizations.
Strong organizational, analytical, and problem-solving skills.
Ability to balance near-term delivery with long-term technical strategy, responsible AI adoption, operational excellence, and team development.

Nice To Haves

Experience building AI-powered solutions for healthcare operations, revenue cycle management, laboratory billing, claims processing, reimbursement, or payer integrations.
Experience developing AI copilots, intelligent agents, or workflow automation solutions that improve operational efficiency and decision-making.
Experience with intelligent document processing (IDP), OCR, natural language processing (NLP), or document intelligence platforms.
Experience working with AI orchestration frameworks and vector databases such as LangGraph, LangChain, Semantic Kernel, Amazon Bedrock Knowledge Bases, Pinecone, OpenSearch, or similar technologies.
Experience working with healthcare standards and transactions including HIPAA, HL7, FHIR, X12, CPT, and ICD-10.
Familiarity with laboratory information systems (LIS/LIMS), molecular diagnostics, or clinical laboratory workflows.
Experience integrating enterprise platforms such as SAP, Salesforce, Workday, Oracle, or similar financial and operational systems.
Experience modernizing legacy business applications through cloud migration, AI-enabled automation, or platform transformation initiatives.
AWS certifications such as Solutions Architect, Developer, or DevOps Engineer.
Experience leading geographically distributed or hybrid engineering teams.
Experience working in regulated healthcare, diagnostics, life sciences, or medical device environments.

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.
Conduct regular one-on-ones, performance reviews, career development planning, and mentoring to support individual growth and team success.
Lead recruiting, interviewing, onboarding, and talent development to build a diverse, high-performing engineering organization.