phoenixtechnologies - Staff Data Platform Engineer, Agentic AI
Requirements
• 10+ years of professional experience in software and data engineering, working with production systems. • Hands-on experience using AI coding agents in your daily development workflow. • Strong experience building event-driven architectures and distributed data pipelines. • Deep experience modeling transactional and behavioral datasets. • Understanding of data requirements for agentic and autonomous systems - including grounding, feature readiness, decision traceability, and feedback loop design. • Strong SQL and experience with distributed/cloud-native systems (AWS or GCP). • Experience working with analytics databases (ClickHouse). • Experience designing systems that require replayability, correctness, and observability. • Comfort working within a TypeScript/Node.js backend ecosystem. • Startup mindset: comfortable owning ambiguous, high-impact domains. • Experience with event streaming platforms (Kafka, Pub/Sub, etc.). • Experience preparing datasets for ML models or working with feature stores. • Familiarity with RAG systems or AI retrieval architectures. • Exposure to ecommerce, payments, or subscription platforms. • ## Leadership Traits We Value • Strong recruiting and talent development capabilities • Product judgment • Calm under pressure • Builder mentality • These are the values that guide how we operate: • All In to Win — Operate with urgency, intensity, and a relentless bar for excellence. • A Players Only — Only hire, develop, and keep A players. Protect talent density. • Merchant First — Merchants are why we exist. Every decision measured by merchant impact. • Entrepreneurial Spirit — Move like a Day One company. Fast, scrappy, hungry. Everyone owns. • Execution Over Ego — Best ideas win regardless of source. Status and titles do not matter.
Benefits
• This is a rare opportunity for a technical leader to step into a company with proven revenue, product-market fit, an established team, and a large market opportunity. • Three things make this an inflection point: • Product-market fit is established. Demand continues to grow, merchant adoption is accelerating, and Phoenix is outperforming expectations. • There is an opportunity to define a category. While many companies are building AI tools for commerce, few are focused on helping sophisticated DTC operators automate revenue-generating decisions at scale. • Our customers are AI-ready. They adopt technology quickly when it drives measurable business outcomes, creating an ideal environment for agentic products.
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