Senior AI Product Builder

Role Description

As a Senior AI Product Builder at ShipBob, you own the full build loop for your product domain: discovery, story/specs, AI-augmented prototypes, and production-ready PRs. This is not the traditional PM role — you are a builder. You use the AI development toolchain (e.g., Claude Code, Driver.ai) to understand ShipBob's codebase architecture, generate working code against the actual repo, and ship to production with minimum engineering rework.

The minimum technical floor for this role is real: you must read ShipBob's data model, evaluate AI-generated scaffolding for correctness, and write story/specs precise enough that AI tools can act on them without follow-up questions.

You will be part of the Sortation Technology team. We build the products behind every point where ShipBob physically sorts inventory:

• Inbound presort at receiving
• Outbound parcel sortation feeding final-mile injection
• B2B freight sortation to build retail or wholesale pallets
• Returns sortation routing units back to inventory or disposition

As volume grows across time-sensitive marketplace and B2B channels, sortation has become a direct lever on merchant outcomes: on-time shipping, marketplace and retailer compliance, inventory accuracy, and the tracking experience end-consumers see. Sortation sits at the intersection of physical operations and digital systems, where small execution gaps compound into merchant-visible failures — making this one of the highest-leverage product surfaces at ShipBob.

This PM owns the products that determine whether units move to the right place, at the right time, and whether what we tell merchants matches what's happening on the floor. This role is for someone energized by speed, uncomfortable with waste, and who measures success by outcomes shipped — not documents approved. You operate in an AI-native pod alongside an AI Engineer, AI/Prompt Engineer, and Designer. This role reports to a Director, AI Product Builder.

What you'll do:

• Own the full product loop independently: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement.
• Conduct customer discovery and use AI tools to synthesize research across tickets, interviews, behavioral data, and competitive signals.
• Demonstrate deep functional and technical knowledge of owned products end-to-end. Demo to merchants and partners; understand competitive landscape and key differentiators.
• Use AI tools to analyze product metrics, identify usage patterns, and surface anomalies. Define success metrics and kill thresholds at spec time without coaching.
• Maintain a prioritized roadmap ranked by impact × speed. Use AI tools to synthesize competitive intelligence, market trends, and customer insight into strategic inputs.
• Evaluate whether a proposed solution fits ShipBob's architecture without Engineering translation. Understand service boundaries, data structures, and how merchant and partner API usage shapes data contracts.
• Route changes through prototype-then-PR. Write clear story/specs and review AI-generated code before raising. PR promotion rate improves consistently.
• Set experiment hypotheses with explicit kill thresholds. Make day-7 rollout/kill decisions on AI-surfaced data.
• Additional duties and responsibilities as necessary.

You'll apply this builder model to one of ShipBob's most operationally critical product surfaces – Sortation Technology.

• Translate merchant, marketplace, and channel requirements into sortation capabilities across the fulfillment lifecycle.
• Sortation performance shapes outcomes for DTC, marketplace, B2B/retail, and returns flows: on-time shipping, marketplace and retailer routing-guide compliance, inventory accuracy, and accurate returns disposition.
• Sequence the roadmap around the highest-impact pain points.
• Close the gap between system signals and physical reality across every sortation surface.
• Sortation failures show up as merchant-visible defects: late shipments, mis-sorts, missing tracking events, mis-routed returns, and inventory inaccuracy at stowing.
• Build the tooling, workflows, and verification signals that prevent them.
• Partner with Operations to turn product into adoption.
• Work directly with FC, Sort Center, Inbound, and Returns leadership, alongside Process Engineering and Transportation.
• Translate new tools into standard operating procedures and measurable performance improvement across every sortation surface — from manual sort to future automated unit sorters.
• Move the metrics that define sortation performance — outbound execution SLAs (Click-to-Collect, Mis-sort Rate, Container Audit Defect Rate), inbound rebuild outcomes (drop-to-stock, SLA adherence), B2B compliance (SLA, load accuracy, retailer routing-guide compliance), and returns processing (cycle time, disposition accuracy).

Qualifications

• 5+ years of product management, product engineering, or equivalent experience, with demonstrated hands-on AI tool usage in a professional context.
• Proven ability to write story/specs that AI tools can act on directly — state machines, business rules, data contracts, edge cases — not narrative PRDs.
• Technical fluency: can read a data model, evaluate an API contract, and identify when AI-generated code deviates from the target architecture.
• Track record of shipping working prototypes or production code, not just Figma mocks or slide decks.
• Strong outcome ownership: sets success metrics and kill thresholds at spec time and tracks them after launch.
• Experience working in supply chain, fulfillment, logistics, transportation, or e-commerce technology. Sortation technology experience is a strong plus.
• Comfortable operating in a fail-fast culture. Being wrong fast is a feature here — staying slow to look right is the failure mode.
• Excellent written communication: you write specs, not meeting notes.

Requirements

• Hands-on experience with the AI development toolchain (e.g., Claude Code, Driver.ai, Cursor, Replit, V0, Figma AI).
• Working knowledge of TypeScript, React, or Python — enough to debug AI-generated code and understand what the Engineer is reviewing.
• Experience with warehouse management systems, order management, carrier integration, or fulfillment operations at scale.
• Prior experience transitioning a product team from traditional SDLC to an AI-native operating model.

Benefits

• Medical, Dental, Vision & Basic Life Insurance
• Paid Maternity/Parental Leave Program
• Paid Holidays & Flexible Time Off Program
• Paid Sick Leave
• Wellness Days (1 day/quarter)
• 401K Match
• Comprehensive Benefits Package