[Hiring] Senior AI Product Builder, Inventory Optimization @ShipBob, Inc.

Role Description

AI Builders is ShipBob’s new job family — the deliberate next step for Product Management in the AI-native era. The thesis is simple: when AI tools can generate working code from precise specs, the slowest step is no longer the spec — it is the PM→Engineer handoff. AI Builders close that gap by owning discovery, specs, prototypes, and production PRs themselves, accelerated by an AI-native pod.

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 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.

Your domain is Inventory Optimization — the decision systems that determine where a merchant's inventory should live across ShipBob's fulfillment network, how much should be positioned at each node, and when to replenish before stockouts or overstock erode margin. IO sits at the intersection of demand forecasting, inventory placement, Promise, and the broader Merchant Tech surface. Placement quality is upstream of delivery speed, fulfillment cost, and the promises ShipBob can make to shoppers — it is one of the highest-leverage product surfaces in the company.

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 talented engineers who are ready to support you and push back on solutions when needed. This role reports to a Director, AI Product Builder.

What you'll do:

• Own the full product loop end-to-end: AI-augmented discovery → story/spec → prototype → production PR → outcome measurement.
• Own the forecasting, placement, and replenishment decision surface end-to-end.
• Run customer discovery yourself; 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.
• Use AI tools to analyze product metrics, identify usage patterns, and surface anomalies.
• Maintain a prioritized roadmap ranked by impact × speed.
• Evaluate whether a proposed solution fits ShipBob’s architecture without Engineering translation.
• Route changes through prototype-then-PR.
• Set experiment hypotheses with explicit kill thresholds.
• Participate in architecture reviews alongside Engineering.
• Additional duties and responsibilities as necessary.

Your first 90 days:

• Days 1–30 — Map the domain.
• Days 30–60 — Ship your first PR.
• Days 60–90 — Make a real call.

Qualifications

• 5+ years of product management, product engineering, or equivalent experience, with demonstrated hands-on AI tool usage in a professional context.
• Demonstrated ability to write story/specs that AI tools can act on directly.
• 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.
• Sound 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.
• Comfortable operating in a fail-fast culture.
• 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 Python, SQL, or TypeScript.
• Experience with inventory planning, demand forecasting, replenishment, or multi-node placement and distribution optimization 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