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

Plenful is hiring a Principal Software Engineer to architect and own the data foundation of Plenful’s next-generation automation platform. This role is singularly focused on building the institutional memory and context graph layer — a greenfield system that will power complex, multi-step workflows, decision tracing, and durable abstractions in a regulated healthcare domain.

This is not a people-manager-first role. It is a foundational systems architect position. Your primary output is durable, scalable data architecture that other teams build on. You will design and ship the context graph + decision tracing system that becomes the backbone of Plenful’s automation platform.

Key objectives:
Architect the domain model, context graph, workflow state, actions, and decision history

Define how institutional memory is represented, versioned, queried, and evolved. Build systems that are expressive enough for AI-driven workflows while remaining governed, testable, and auditable. Ensure the platform scales from approximately 90 customers today to 200+ without degrading reliability. Reduce hero-dependence by building abstractions that prevent constant escalations.

• Define the canonical data model for workflows, context, actions, and outcomes.
• Design durable abstractions across automation, decision tracing, and system memory.
• Establish clear system boundaries across feature-based teams.

• Architect a graph-backed representation of state, history, and reasoning.
• Enable traceability of decisions across complex healthcare workflows.
• Ensure schema evolution supports regulatory scrutiny and auditability.

• Design state management systems across AWS, Postgres, Python, and Temporal workflows.
• Drive performance, reliability, and scalability across high-throughput workflows.
  
  Own normalization tradeoffs, indexing strategy, and access pattern design.

• Establish standards for schema versioning, lineage, testing, and data integrity.
• Build systems that reduce incident frequency and escalation dependency.
• Partner with tech leads across feature teams to enforce architectural coherence.

The Principal Engineer will oversee the Praxis/context graph layer team, partnering closely with product and feature team leads. Stack includes AWS, Postgres, Python, React, Type Script, and Temporal. The workflow engine is highly expressive and enables customers to write workflows using Claude. Strong evaluation pipelines allow rapid model iteration, with a recent model upgrade driving 20-30% improvement overnight. The broader engineering team is scaling from 20 to 40 within a year.

The organization is moving from horizontal teams (backend, frontend, Dev Ops) to feature-based teams with tech leads.

A scalable, well-governed context graph system that becomes a competitive moat. Reduced escalations and fewer hero-driven interventions. Clear data boundaries that allow feature teams to ship rapidly…