Engineer V - Software
PODS · Clearwater, FL · Today
HybridFull-time
Job Summary As a Software Engineer V, you set technical direction. You own architecture that spans teams — designing the systems others build within — and you are accountable for technical outcomes delivered through others as well as by your own hands. You define the problems as much as you solve them: turning ambiguous business goals into technical strategy, sequencing multi-quarter initiatives, and making the build-vs-buy and migration calls that shape the platform for years. You are still hands-on. You prototype the risky parts, write the critical-path code, and stay close enough to production reality that your designs survive contact with it. And you shape how we test and learn at scale — building platforms where experimentation is cheap, so every team can iterate on price display, communications, chat, and beyond with real customer data. A Day in the Life Technical Direction: Own the target architecture for a platform or domain that spans multiple teams. Author and drive the technical proposals and design reviews that align engineers around it. Force Multiplication: Mentor senior engineers, not just early-career ones. Raise the bar org-wide through reusable patterns, standards, and incisive design review. Hands-On Delivery: Prototype novel or high-risk components and ship critical-path code. Your credibility comes from working software, not slides. Operational Excellence: Define SLOs and the reliability strategy for your domain. Lead retrospectives on major incidents and turn them into architectural improvements. Test and Learn at Scale: Shape the experimentation strategy for your domain and build systems that make running a test a config change, not a project. Momentum: We work in short cycles, code released in days, experiments read out weekly, priorities adjusting as results come in. You design the architecture that makes this speed safe — systems where shipping fast and shipping well are the same motion. Strategic Partnership: Work with Product, leadership, and across organizations to align technical strategy with the business roadmap; make and defend build/buy/migrate decisions. Responsibilities Architecture Ownership: Design and evolve systems spanning team boundaries; define the integration contracts and domain boundaries other teams build against. Migration Leadership: Plan and lead incremental, zero-downtime migrations off legacy systems while the business keeps running. Technical Risk Management: Identify the riskiest assumptions in a multi-quarter initiative early, and design spikes and milestones that retire them fast. Engineering Standards: Own key parts of the software design process, review culture, and production-readiness bar across your domain. Hiring Bar: Help design interview loops and calibrate the technical bar for senior hires. Our Tech Stack Front-end: React, Vite, Next.js, TypeScript. Back-end: Kotlin, Spring Boot, PostgreSQL. Cloud & Infrastructure: Microsoft Azure (Kubernetes, Functions, Front Door), Docker, Helm. Data & Analytics: Snowflake, Salesforce CDP. Experimentation & Observability: Eppo, Datadog. DevOps: Azure DevOps (ADO), Pipelines. AI Tooling: Cursor, Claude. Qualifications Basic Qualifications Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience). Experience: 8+ years of professional software engineering experience, including leading multi-quarter technical initiatives that spanned multiple teams. Distributed Systems: A track record of designing, operating, and evolving distributed systems in production at meaningful scale. Cloud Architecture: Deep expertise in cloud-native architecture (Azure preferred): microservices, eventing, API design, and the failure modes of each. Design Communication: Exceptional written design skills — you can align a dozen engineers through a document. Preferred Qualifications Experience as the founding or lead architect of a platform other teams build on. Experience with data-warehouse-native experimentation (Snowflake) and observability at scale (Datadog). Fluency with AI-assisted development workflows (e.g., Cursor).