My products engage millions of annual visitors and registered developers across the full lifecycle — from platform discovery and education through app monetization.
I directly manage engineering teams shipping production software to internal and external developers — defining the “what” and “why” while directly leading my engineering team on the “how.” My career has been built on translating complex technical systems into business strategy, aligning stakeholders across matrixed organizations, and shipping products that drive measurable outcomes.
What I do:
- Define product vision, multi-year roadmaps, and go-to-market strategy
- Directly manage engineering teams shipping production software (engineering, data engineering, BIE, TPM, product)
- Make architecture decisions and buy-vs-build evaluations for platform investments
- Drive adoption of AI/ML capabilities — LLM product strategy, RAG systems, agentic AI workflows, ML-powered segmentation and personalization
- Align stakeholders across business units in matrixed enterprise environments
How I work: I use AI-assisted prototyping tools (Kiro, Claude Code, CrewAI, MCP) to sharpen specs and accelerate engineer handoff — prototypes give my engineering team a concrete starting point rather than a spec document. From PRFAQ-generation pipelines to personal chief-of-staff automations, I prototype product ideas at personal scale so the decisions I bring to engineering are sharper. Open-source examples at github.com/joegarvey-ai.
Domains: AI/ML products, marketing technology, enterprise data platforms, developer tools, B2B SaaS
Open to connecting on product leadership, AI/ML strategy, and MarTech.
Amazon
Senior Manager, Product Management
Head of Amazon Developer Technology. Directly managing a 16-person horizontal team shipping production software to internal and external developers — engineers (with an SDM direct report), technical product managers, technical program managers, business intelligence engineers, data engineers, and marketing operations specialists across multiple time zones. Our products span the full developer lifecycle — acquisition, education, and monetization enablement — while providing the analytics and attribution infrastructure that internal teams use to optimize channel performance.
Defining product strategy for a portfolio of first-party and third-party products serving multiple Amazon Devices & Services business units. Key focus areas include AI-powered developer tools, enterprise data platforms, and content velocity infrastructure.
Current strategic priorities:
- Defining the team's intelligence layer strategy, organizing initiatives across unified developer intelligence, contextual knowledge delivery, and content velocity
- Shipping concurrent AI-powered products — including an agentic developer assistant (launched June 2026, upgrading from a single-model Q&A chatbot to a multi-agent system that partner teams can extend), an LLM-powered Voice of Customer feedback platform, and a natural-language-to-SQL data access agent — with quality-bar gating that has paused one launch for accuracy issues engineering metrics had not caught
- Led a cross-org decision with partner engineering teams to consolidate competing AI retrieval products for developers into a single customer-facing product, now generally available to external partners — my team owns the underlying documentation and knowledge layer that powers it
- Leading a horizontal team spanning engineering, data engineering, business intelligence, technical program management, and marketing operations
- Establishing hub-and-spoke operating model for shared technology infrastructure across the organization
- Defining measurable quality acceptance criteria for RAG/LLM products (retrieval precision, actionability, follow-through) as release gates rather than aspirational goals
Head of MarTech & Analytics
Led a MarTech team within Amazon's Devices Business Development, Tooling, Education & Technology organization, focused on enabling external developers to succeed on Amazon devices. Owned the marketing technology and analytics infrastructure that the org relied on for full-funnel attribution, channel-mix optimization, and developer lifecycle measurement.
Owned product vision and requirements across AI-powered developer tools, marketing analytics, and audience segmentation platforms.
Key contributions:
- Defined product vision and measurable quality acceptance criteria for a RAG-based developer assistant chatbot, partnering with ML engineering to deliver LLM-powered resource discovery over a documentation corpus of roughly 14,000 pages
- Led strategy for GenAI Voice of Customer platform unifying unstructured feedback across 20+ channels with AI-driven sentiment analysis and automated triage
- Drove 3-year rolling roadmap defining buy-vs-build decisions across the product portfolio; established hub-and-spoke operating model with standardized technology evaluation criteria
- Directed AWS resource consolidation and tool deprecation to reduce engineering maintenance overhead
Senior Product Manager, Data Technology
Defined vision, strategy, and prioritization for an enterprise data technology team of software engineers, data engineers, data scientists, and analysts serving Alexa Enterprise sales and marketing teams.
Key contributions:
- Led data architecture strategy to deliver enterprise analytics platform unifying datasets across internal and external sources into a governance-certified single source of truth
- Defined ML segmentation platform strategy with data science team, delivering self-service targeting capabilities that reduced segment creation time and improved campaign performance
- Directed B2B developer registration UX redesign with GDPR-compliant email opt-in system
- Managed team of business intelligence engineers; mentored team members through promotion cycles
Senior Product Manager, Marketing Technology
Defined product strategy and led technical roadmap for MarTech capabilities serving the Alexa Enterprise B2B marketing team. Partnered with engineering and data science teams to deliver data infrastructure and marketing personalization solutions.
Key contributions:
- Defined ML-driven developer targeting strategy with data science team, classifying Alexa builders into audience cohorts that outperformed manual segments in conversion
- Directed Adobe Target web personalization for active developers, partnering with engineering on first-party data integration
- Designed integration architecture connecting marketing, events, webinar, and sales systems; led engineering team delivery
- Established strategic roadmap spanning web and data infrastructure, aligning cross-functional stakeholders on quarterly and annual priorities
- Led requirements and managed engineering sprints across software engineering and business intelligence teams
Senior Marketing Operations Manager
Defined strategic plans and annual roadmaps for marketing technology, analytics, and campaign operations serving Amazon's Alexa and Amazon Fuse B2B teams. Led requirements definition and managed data science, engineering, and agency partners to deliver measurement and automation solutions.
Key contributions:
- Defined ML-based multi-touch attribution model with data science team, identifying key channel drivers and enabling reallocation of marketing budget to higher-performing channels
- Designed self-service campaign tracking tool that automated trackable link creation for campaign managers, eliminating attribution errors
- Led requirements and engineering delivery for marketing-to-data-warehouse pipelines enabling automated reporting across email and web channels
- Directed launch of AmazonFuse.com (customer-facing brand and website), managing agency RFP, content and UX strategy, and engagement reporting
- Led launch of enterprise partner-facing creative asset repository, including agency management, privacy compliance, and cross-org stakeholder alignment
- Served as subject matter expert for marketing technology stack, advocating for new tools and leading training across the marketing function
Edelman
Senior Account Supervisor, Microsoft
Led digital strategy for Microsoft global brand at Assembly Media (Edelman Digital's dedicated Microsoft agency). Managed cross-functional teams of creatives, planners, paid media specialists, and analysts across concurrent client engagements.
- Directed adoption of ad serving, dark social tracking, and data management platform (DMP) technologies across the Microsoft client team
- Grew agency's Microsoft business significantly through data-driven recommendations, securing additional creative and analytics projects
- Managed multi-project team labor and expense budgets; led cross-functional teams on a workload of 4–10 Microsoft projects per quarter
Digital Account Supervisor, Microsoft
- Managed digital marketing and measurement strategy for Microsoft client engagements. Promoted to Senior Account Supervisor within 18 months.
Razorfish
Senior Account Manager, Nike
- Led integrated campaigns for Nike Football, Soccer, and Action Sports. Managed team of 20 for Nike's Super Bowl campaign, directing social budget, targeting strategy, and real-time optimization. Promoted from Account Manager within one year.
Account Manager, Nike
- Managed integrated display, video, and social campaigns across Nike sport categories, serving as digital creative project manager and ad strategist for product launch and athlete-focused campaigns.
Technical Skills
AI/ML & GenAI Strategy
LLM product strategy, RAG system design & requirements, agentic AI workflow strategy, ML product applications (segmentation, personalization, sentiment analysis), AI product roadmapping & vendor evaluation
Data & Analytics
SQL (intermediate), Tableau, QuickSight, A/B testing, multi-touch attribution modeling, data warehouse strategy, ETL pipeline requirements, privacy compliance
Marketing Technology
Adobe Experience Cloud (Analytics, Target, Launch, AEM), Salesforce Marketing Cloud, Marketo, Customer Data Platforms (CDP), first-party data strategy
Cloud & Infrastructure Strategy
AWS architecture strategy (Redshift, S3, Lambda, CloudFront), API integration strategy, scalability planning, cost optimization
AI-Assisted Prototyping
Kiro, Claude Code, CrewAI agent orchestration, MCP (Model Context Protocol) integration — used to prototype product concepts, sample data models, and PM artifact generation pipelines at personal scale to accelerate engineer handoff (portfolio: github.com/joegarvey-ai)
Education
- University of Kansas — B.S. in Journalism: Strategic Communication 2007 — 2011
Double Minor: Philosophy & Communications
Certifications
- AWS Certified Database: Design & Deployment — Amazon Web Services 2021
- Adobe Analytics Certification — Adobe 2020
- Digital Marketing Analytics — MIT Sloan School of Management 2018