Principal Software Engineer

PaulHood is transforming the mid-market CPA industry through a year-round membership model supported by modern technology and processes. The Principal Software Engineer will establish technical direction and build integrations, workflow automations, reusable engineering standards, and quality engineering practices. The role will also support reliable software delivery and future AI-enabled workflows.

Responsibilities:

• Reverse-engineer and stabilize existing business-critical workflow automations, regardless of the platform on which they were built
• Document workflow purpose, dependencies, credentials, failure modes, business owner, technical owner, monitoring, and recovery procedures
• Design and build integrations using APIs, webhooks, event-driven patterns, scheduled jobs, low-code tools, and custom services where appropriate
• Establish standards for source control, testing, CI/CD, secrets management, observability, alerting, auditability, retries, and recovery
• Create reusable connectors and patterns for common PaulHood systems and acquisition integration needs
• Define when work belongs in a workflow platform, custom code, or the data platform, based on business criticality, maintainability, complexity, security, and operating cost
• Establish the initial Quality Assurance and quality engineering practice for the future Software Engineering department
• Define an automation-first test strategy covering unit, API, contract, integration, end-to-end, regression, and appropriate non-functional testing
• Build and maintain test automation frameworks using tools such as Playwright, Cypress, Selenium, pytest, Jest, Postman/Newman, or comparable technologies
• Integrate automated tests and quality gates into CI/CD pipelines so quality is evaluated continuously rather than at the end of delivery
• Create test-data, test-environment, defect triage, release-readiness, and regression practices that can scale with the engineering organization
• Define quality metrics such as automated coverage by risk area, defect escape rate, flaky-test rate, time to detect, regression duration, and release failure patterns
• Coach software engineers to own quality. The QA practice should enable engineering quality, not become a downstream testing queue
• Support future AI-enabled workflows using LLM APIs, tool calling, MCP or comparable protocols, structured outputs, approval controls, and auditability
• Apply software quality principles to AI workflows, including evaluation, regression testing, deterministic controls where possible, monitoring, and human review for high-impact actions

Requirements:

• 10+ years of hands-on software engineering experience, with demonstrated technical ownership and decision-making at a Principal, or equivalent level required
• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related technical field required
• Strong backend development skills using Python, TypeScript, or comparable technologies
• Proven experience designing and building production-grade integrations across multiple systems
• Deep knowledge of REST APIs, webhooks, authentication and authorization patterns, service accounts, rate limiting, retries, idempotency, and resilient error handling
• Hands-on experience with one or more workflow or automation platforms, such as Power Automate, Workato, n8n, Okta Workflows, Zapier, Make, or similar tools. Experience with a specific platform is less important than the ability to work across technologies
• Strong experience with Git, automated testing, CI/CD, logging, monitoring, alerting, secrets management, production troubleshooting, and root-cause analysis
• Meaningful hands-on experience designing and implementing automated testing frameworks and strategies
• Experience integrating automated tests and quality controls into CI/CD pipelines
• Experience helping establish, mature, or materially improve Quality Engineering practices, standards, or processes
• Working knowledge of identity and security concepts, including provisioning, deprovisioning, RBAC, least privilege, audit trails, and sensitive-data handling
• Strong SQL skills and sufficient data architecture knowledge to integrate operational and analytical environments safely and reliably
• Ability to independently evaluate complex problems and make sound architecture and technology decisions
• Demonstrated ability to communicate technical concepts, risks, and recommendations clearly to both technical and nontechnical stakeholders
• You enjoy building new capabilities and taking a hands-on approach to solving problems
• You are comfortable navigating ambiguity, investigating unfamiliar systems, identifying risks, and recommending a path forward
• You balance technical sophistication with maintainability, cost, security, risk, and business value
• You think holistically about how applications, identities, APIs, data, automation, testing, and business processes interact
• You view quality as an essential part of software engineering and build it into the development process
• You are naturally curious and solutions-oriented, asking thoughtful questions and continuously looking for ways to improve how work gets done
• You work independently and take ownership while collaborating effectively across teams and functions
• You focus on scalability by creating patterns, standards, documentation, and tools that make future challenges easier to solve