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Staff Data Platform Engineer, Agentic AI

Role overview

Qualifications

  • 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.

Responsibilities

  • Build the AI Data Layer.
  • Power Real-Time Decision Systems.
  • Build Closed-Loop Feedback Systems.
  • Drive Business Impact Through Data Strategy.

About the company

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Phoenix Technologies

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Job description

Phoenix is the Autonomous Commerce Platform for DTC Founders. We unify storefronts, checkout, payments, and operations into one platform where AI agents handle the operational grind and merchants focus on growth.

We set out to build the "Shopify of Direct Response" and along the way recognized something bigger. Direct response is roughly a third of all ecommerce transactions, a trillion-dollar market chronically overlooked by Silicon Valley. The merchants who run it are obsessive about tooling. 

They live and die by velocity, conversion, and margin. They have no brand moats. They only compete on operations, which is exactly what makes them ripe for agentic disruption and the earliest, fastest adopters of AI agents in commerce.

That insight reframed Phoenix from "the Shopify of DR" to the AI Agent Platform for DTC Founders.

This is a category-defining bet, and we are running at it from a position of strength.


Where We Are Today
  • 8-figure ARR growing 100%+ YoY

  • Strong unit economics and efficient growth

  • Rapid merchant adoption and expanding market presence

  • Backed by experienced operators and investors with a history of building and scaling successful businesses


  • Why Now

    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:

    1. Product-market fit is established. Demand continues to grow, merchant adoption is accelerating, and Phoenix is outperforming expectations.

    2. 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.

    3. Our customers are AI-ready. They adopt technology quickly when it drives measurable business outcomes, creating an ideal environment for agentic products.


    The Role

    We are hiring a Staff AI Data Engineer to design and own the data foundation behind Phoenix’s agentic commerce platform.

    This role is responsible for turning raw commerce events - transactions, payment attempts, subscriptions, funnels, merchant actions - into structured, decision-grade intelligence that powers:

  • Autonomous payment routing

  • Approval probability scoring

  • Checkout optimization agents

  • Merchant copilots grounded in real data

  • Future predictive and adaptive systems

  • This is not analytics. This is production decision infrastructure.

    You will architect the event models, pipelines, and data contracts that allow AI agents to observe, reason, act, and improve in real time. You will design for low latency, high correctness, replayability, and observability - because autonomous systems cannot rely on fragile data.

    This role sits at the center of platform, payments, and AI - defining how intelligence is embedded into core commerce behavior and how Phoenix’s systems learn from every transaction to continuously improve merchant performance.


    What You'll Own

    Build the AI Data Layer

    Design and own canonical data models across transactions, subscriptions, customers, payment attempts, and merchant behavior. Build event-driven pipelines that transform operational data into structured, replayable intelligence layers with strong guarantees around validation, ordering, idempotency, and observability.

    Power Real-Time Decision Systems

    Design low-latency data layers and clear data contracts that power autonomous routing, approval scoring, and checkout optimization. Ensure decision traceability and correctness so AI agents can operate safely in production commerce flows.

    Build Closed-Loop Feedback Systems

    Create outcome-tracking and feedback pipelines that allow systems to learn from every transaction. Enable experimentation, measurement, and continuous optimization across merchants while preserving data isolation and platform integrity.

    Prepare the Platform for Adaptive ML

    Develop feature-ready datasets and behavioral schemas that support predictive systems such as routing optimization and churn risk. Lay the groundwork for feature stores and safe model iteration without disrupting live decision infrastructure.

    Drive Business Impact Through Data Strategy

    Set the technical direction for how Phoenix models, measures, and activates commerce intelligence. Collaborate cross-functionally with checkout, payments, and AI teams to translate business problems into structured signals that measurably improve approval rates, conversion, retention, and merchant growth.


    What We're Looking For

    Required

  • 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.

  • Preferred

  • 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
  • High ownership

  • Decisiveness

  • Strong recruiting and talent development capabilities

  • Accountability

  • Product judgment

  • Calm under pressure

  • Builder mentality


  • Culture

    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. 

  • Apply once. Then go straight to the hiring manager.

    After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.

    MR

    Marcus Rivera

    Chief Revenue Officer

    m.rivera@company.com
    linkedin.com/in/marcusrivera
    Unlocked after you apply
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