Senior Product Manager - Tech, FBA AI Science & Analytics

Amazon; Bellevue (WA); On-site; USD 151,000 - 205,000; Full time

Job summary

Amazon in Bellevue, WA is seeking a Product Manager Tech within the FBA AI Science and Analytics organization to lead GenAI initiatives at scale, building semantic data layers, anomaly detection, and data deep-dive agents that empower seller-facing apps.

You will own the product roadmap, partner with applied scientists and engineers, define evaluation frameworks, and drive measurable AI-driven productivity across high-frequency seller workflows.

Qualifications

• 7+ years of technical product or program management experience.
• Experience owning/driving roadmap strategy and definition.
• Experience with feature delivery and tradeoffs of a product.
• Experience contributing to engineering discussions around technology decisions and strategy related to a product.
• Experience representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning.
• Bachelor's degree in a quantitative/technical field such as CS/engineering/statistics.

Responsibilities

• GenAI Product Strategy & Roadmap: Define and execute the product vision for LLM-powered science and data agents, spanning prompt engineering strategies, retrieval-augmented generation (RAG) architectures, semantic parsing, and agent orchestration frameworks that enable autonomous reasoning at scale.
• Semantic Layer & Knowledge Graph Design: Own the product requirements for FBA's centralized semantic layer, defining ontologies, entity-relationship schemas, disambiguation logic, and machine-readable metadata standards that LLMs consume to produce accurate, governed outputs.
• LLM Agent Development: Partner with applied scientists and engineers to design, evaluate, and ship production LLM agents across multiple FBA domains for internal and seller-facing applications.
• Stakeholder & Science Partnership: Work closely with the science and tech teams on model selection, fine-tuning strategies, retrieval pipeline optimization, and agent loop engineering.
• Metrics & Evaluation: Define success metrics grounded in agent accuracy, query correctness, latency, coverage, and real time-savings.
• Rapidly Evolving AI Landscape: Stay current with advances in foundation models, agentic architectures, harness engineering, semantic parsing, and enterprise AI tooling.

Skills

Roadmap strategy

Product delivery

Engineering collaboration

Executive stakeholder advocacy

Education

Bachelor's degree in quantitative/technical field

Tools

SQL

Tableau

Python

Advanced Excel

Job description

Description

FBA AI Science and Analytics accelerates FBA's AI-native transformation by building, integrating, and scaling AI-powered data & science products and seller-facing experiences that drive operational efficiency and growth across Fulfillment by Amazon globally. We're seeking a creative, industrious, customer-obsessed PM who is passionate about applying GenAI techniques to solve real-world data and science challenges at scale.

Description

FBA AI Science and Analytics accelerates FBA's AI-native transformation by building, integrating, and scaling AI-powered data & science products and seller-facing experiences that drive operational efficiency and growth across Fulfillment by Amazon globally. We're seeking a creative, industrious, customer-obsessed PM who is passionate about applying GenAI techniques to solve real-world data and science challenges at scale.

As a Product Manager Tech in our FBA AI Science and Analytics organization, you will lead the strategy and execution of multiple critical GenAI initiatives, including but not limited to: (1) a Semantic Data Layer that delivers semantically consistent, disambiguated data through a machine-readable interface to every AI application across FBA—eliminating per-application integration costs, metric re-derivation, and the concept-entity ambiguity that drives inaccurate AI outputs; (2) an AI-Powered Anomaly Detection system that autonomously identifies, diagnoses, and surfaces data quality issues and business metric anomalies; and (3) a Data Deep-Dive Agent that autonomously investigates business questions through data mining—surfacing root causes, trend shifts, and actionable insights without manual exploration.

You will drive product innovation across unified, secure, and intelligent AI solutions used by seller-facing application builders across FBA, as well as end-to-end AI-native experiences that solve high-frequency seller workflows — from inventory optimization and inbound efficiency to demand shaping and capacity planning. Your work will directly shape a future where AI is not a separate tool for sellers to adopt, but a native layer woven into every seller's decisions, operations, and growth strategies — delivering actionable insights in minutes rather than days.

Key job responsibilities

• GenAI Product Strategy & Roadmap: Define and execute the product vision for LLM-powered science and data agents, spanning prompt engineering strategies, retrieval-augmented generation (RAG) architectures, semantic parsing, and agent orchestration frameworks that enable autonomous reasoning at scale. Collaborate with scientists to evaluate trade-offs between fine-tuned domain models and in-context learning approaches for optimal accuracy-latency balance.
• Semantic Layer & Knowledge Graph Design: Own the product requirements for FBA's centralized semantic layer, defining ontologies, entity-relationship schemas, disambiguation logic, and machine-readable metadata standards that LLMs consume to produce accurate, governed outputs. Work with scientists to develop techniques that minimize hallucination in downstream agents.
• LLM Agent Development: Partner with applied scientists and engineers to design, evaluate, and ship production LLM agents across multiple FBA domains for internal and seller-facing applications. Define evaluation frameworks incorporating composite accuracy metrics, confidence calibration, chain-of-thought verification, guardrails, and human-in-the-loop fallback mechanisms.
• Stakeholder & Science Partnership: Work closely with the science and tech teams on model selection, fine-tuning strategies, retrieval pipeline optimization, and agent loop engineering. Translate research advances in LLMs, tool-use, and multi-agent systems into shippable product features.
• Metrics & Evaluation: Define success metrics grounded in agent accuracy, query correctness, latency, coverage, and real time-savings. Own end-to-end evaluation including LLM-as-judge frameworks, human evaluation protocols, and A/B experimentation for agent capabilities.
• Rapidly Evolving AI Landscape: Stay current with advances in foundation models, agentic architectures, harness engineering, semantic parsing, and enterprise AI tooling. Identify and prototype emerging capabilities—such as multi-step reasoning, self-improving agents via reflection loops, structured generation with constrained decoding, and tool-augmented inference—for incorporation into the product roadmap.

A day in the life

Your day-to-day responsibilities will include conducting user research, analyzing adoption and productivity data, and making data-driven decisions to guide product development. You'll oversee the entire product lifecycle, from initial concept through launch and iteration, ensuring that products meet quality standards, earn user trust, and deliver measurable business value. You'll partner closely with engineering and science teams to define v1 experiences that prove concepts quickly, measure impact in real time, and stop what isn't working even when it's popular. Additionally, you'll be responsible for developing launch plans, creating product documentation, and establishing processes for measuring and reporting on product performance, adoption metrics, and AI-driven productivity outcomes.

Basic Qualifications

• Bachelor's degree in a quantitative/technical field such as computer science, engineering, statistics
• Experience owning/driving roadmap strategy and definition
• Experience with feature delivery and tradeoffs of a product
• Experience contributing to engineering discussions around technology decisions and strategy related to a product
• 7+ years of technical product or program management experience
• Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning

Preferred Qualifications

• Experience in building and driving adoption of new tools
• Experience with data analysis tools such as Advanced Excel, SQL, Tableau, Python
• Experience in project management methodologies, business analysis, or process improvement

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&DD insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 151,200.00 - 204,600.00 USD annually

Company

Amazon.com Services LLC

Job ID: A10519789