Principal Software Engineer

About Plenful Plenful is on a mission to move pharmacy forward through intelligent automation. We build AI-powered software that eliminates administrative burden, strengthens compliance, and unlocks revenue across critical pharmacy workflows, solving one of the biggest challenges in healthcare today: delayed patient care. Built by a passionate team of former healthcare operators and world-class AI technologists, Plenful combines deep domain expertise with enterprise-grade technology to automate complex workflows across intake authorization, 340B program optimization, and pharmacy revenue reconciliation. Our AI platform is trusted by 95+ leading healthcare organizations to power smarter, faster, and more resilient pharmacy operations. Backed by leading investors including Notable Capital, Bessemer Venture Partners, and TQ Ventures, Plenful is building the institutional memory for healthcare and powering the most complex, highest ROI healthcare workflows. We’re actively hiring as we continue to scale. Learn more about our values and origin story at https://www.plenful.com/company . The Mandate We are seeking a Principal Software Engineer to lead the design and development of core data systems that power a scalable automation platform. This role focuses on building foundational infrastructure for managing complex workflows, system state, and historical data in a high-reliability environment. This is a highly technical, hands-on role centered on system architecture and platform design. You will create durable, extensible data models and services that enable other engineering teams to build efficiently and safely on top of a shared foundation. What You’ll Own Data Architecture & System Design Define and evolve core data models for workflows, system state, actions, and outcomes Design scalable, maintainable abstractions across platform services Establish clear boundaries between systems and services to support team autonomy State Management & Data Systems Architect systems for managing workflow state and historical data across distributed infrastructure Ensure high performance, reliability, and scalability for high-throughput systems Make informed tradeoffs in data modeling, indexing, and access patterns Traceability & Data Integrity Design systems that support traceability and observability of system behavior Ensure data models and storage systems support auditing, versioning, and evolution over time Build mechanisms to maintain data consistency and integrity Engineering Standards Establish best practices for schema management, testing, and data quality Improve system reliability and reduce operational overhead through strong architectural patterns Collaborate with engineering teams to maintain consistency across the platform Environment & Technical Context Cloud infrastructure (e.g., AWS) Relational databases (e.g., Postgres) Backend services (e.g., Python) Workflow orchestration systems Modern frontend technologies (e.g., React, TypeScript) What Success Looks Like Scalable and reliable data systems that support growing product and customer needs Clear and maintainable architecture enabling faster development across teams Reduced operational burden through improved system design and reliability Strong data governance and consistency across the platform Ideal Background Must Have 12+ years owning data architecture in large-scale production systems. Deep relational database and distributed systems expertise. Strong experience evolving schemas in complex, regulated domains. Clear judgment on normalization vs. denormalization, performance tradeoffs, and system boundaries. Experience handling mission-critical incidents in production. Comfort operating in ambiguous, fuzzy problem spaces. Hands-on coding ability in a Python-heavy backend environment. Strong reliability instincts, including observability, testing, and QA rigor. Nice to Have Experience in healthcare, fintech, or infrastructure environments. Exposure to or experience with m