Technical Product Manager, AI

About SpangleAI

Launched in 2025, Spangle AI is the agentic conversion layer connecting AI-led discovery to real-time conversion. We've partnered with enterprise brands like REVOLVE, Alexander Wang, and Steve Madden, delivering up to 50% conversion lifts and 2x ROAS improvements.

We recently closed a $15M Series A. Spangle won NRF’s VIP (Vendor in Partnership) Award for Best AI-Driven Marketing Solution and was recognized in Business of Fashion’s AI startups to Watch.

Founded by serial entrepreneurs with 30+ years scaling AI and commerce at Amazon, Saks, and Gap, we're building the commerce infrastructure for the agentic era, where ChatGPT Shopping, Google AI Overviews, and Meta are reshaping how consumers discover and buy.

Position Overview:

We are seeking an exceptional AI Product Manager who is passionate about building at the frontier of AI and commerce - and who wants to stay hands-on. This is not a spec-and-delegate role. You will personally research emerging AI capabilities, design and run pilots with real merchants, dig into experiment data yourself, and iterate rapidly from prototype to production feature.

This role primarily focuses on: building net-new product lines from first principles - you'll own the full loop of opportunity research, detailed product and system design, hands-on prototyping, live merchant experimentation, and shipping to production in close partnership with engineering, working in an agentic, AI-native way (designing with AI tools, prototyping with coding agents, and automating your own workflows).

You will work directly with founders, engineers, and design partners - owning features from first hypothesis through A/B test readout to GA launch.

This role is ideally based in Seattle, the Bay Area, or Austin, with flexibility for exceptional candidates.

Key Responsibilities:

• Zero-to-One System Building: Identify emerging opportunities at the intersection of AI and commerce, and take them from open question to working product. Define the system architecture at the product level - data inputs, AI/agent pipelines, merchant-facing surfaces, and feedback loops - before a single ticket is written.
• Detailed Product Design: Proactively produce the artifacts that let engineering move fast: detailed specs, edge-case analysis, data schemas, evaluation criteria, and UX flows. You drive design depth without being asked, and you pressure-test your own designs by prototyping them first.
• Hands-On Prototyping & AI-Native Workflow: Build working prototypes yourself using AI coding agents and modern tooling (Claude Code, Cursor, LLM APIs) to validate feasibility and de-risk designs before committing engineering resources. Automate your own research, analysis, and reporting workflows as a matter of habit.
• Experimentation & Measurement: Own experiment design end-to-end - pilot structure, variant assignment, success criteria, statistical rigor, and multi-source measurement (ad platforms, analytics, first-party data). Get into the data directly with SQL and notebooks; when the measurement you need doesn't exist, build it.
• Merchant Pilots: Design and personally operate live pilots with enterprise retail brands. Monitor performance daily, diagnose anomalies down to the funnel and item level, and make fast, evidence-based go/no-go calls.
• Ship with Engineering: Partner closely with engineering to turn validated prototypes into production systems - scoping, sequencing, and iterating in tight loops rather than handing off documents. Serve as the voice of the merchant and the data throughout.

Qualifications:

What we care about most:

• Relentless curiosity and detail obsession. You genuinely want to figure things out - reading the docs, querying the data, prototyping the flow, and tracing an anomaly to its root cause - rather than delegating the understanding to others. This is the one requirement we won't compromise on.
• High agency. You create structure in ambiguity, produce detailed designs without being asked, and default to building and testing over writing documents.

Experience:

• 2+ years in product management, or equivalent experience building and shipping products in engineering, data, analytics, or founder roles. We weight the demonstrated zero-to-one ownership over years of tenure.
• A track record (professional or personal) of taking something from hypothesis → prototype → launch, with evidence of decisions made from data.
• MBA preferred; background in e-commerce, adtech, martech, or retail technology is a plus.

Technical Skills:

• Hands-on fluency with AI-native tooling - prompt engineering, LLM APIs, and coding agents such as Claude Code, Cursor, and Codex; you use them daily, not occasionally.
• Working proficiency in SQL and comfort analyzing data independently (BigQuery, GA4, or similar), or demonstrated ability to get there fast with AI assistance; Python is a plus.
• Strong experimentation fundamentals: statistical significance, sample sizing, funnel and cohort analysis.
• Ability to produce detailed technical product designs - data models, pipeline logic, API-level thinking - and engage credibly with engineers on architecture trade-offs.
• Understanding of ad platforms (Meta, Google) and commerce infrastructure (catalogs, feeds, pixels, structured data) is a strong plus.

Benefits:

• Competitive salary and equity options.
• Comprehensive health benefits package.
• Opportunity to define the AI product direction at a fast-growing startup as a founding team member.
• Direct access to founders, customers, and real production data from day one.