Product Manager I: AI-Driven Digital Solutions Lead

ASM Research, An Accenture Federal Services Company

Utah

On-site

USD 70,000 - 95,000

Full time

2 days ago

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Job summary

ASM Research, An Accenture Federal Services Company, seeks a Product Manager I to drive strategy, definition, and delivery for AI-enabled products. You will connect stakeholders, developers, and end-users to deliver value within the governance framework and security requirements.

You will gather requirements, manage lifecycle, and produce PRDs, backlogs and user stories, working across teams to ensure timely, quality releases and adoption. Experience with AI/GenAI and Agile is preferred.

Qualifications

Bachelor’s degree and 2-5 years of related experience.
Experience in Product Management for digital products using AI or Generated-by-AI preferred.
Experience with Agile/Scrum methodologies preferred.
Experience gathering and documenting business/functional requirements and delivering digital products.
Agile certification preferred.
Pragmatic Institute Product Management Certification or Certified Product Manager preferred.

Responsibilities

Gathers, documents, manages and validates organizational strategy and product requirements from internal stakeholders and users into product deliverables.
Defines and manages the product lifecycle and expectations regarding scope, timelines, and resource constraints to ensure investment in areas that support long-term business needs.
Supports the gathering and assembling of well-vetted evidence to produce an analysis of alternatives (AoA) as inputs for build vs. buy decisions by IT Governance Council (ITGC).
Creates, manages and refines product requirements documents, product backlog, user stories, acceptance criteria, functional requirements, personas, UX/design, and other supporting documentation as required to a product build via Gen AI coding or agile development, or acquiring a product from a vendor.
Supports application of ASM responsible-AI governance to every AI-enabled feature across the full product lifecycle including model risk assessment, human-in-the-loop review, CUI-appropriate data handling, and bias, explainability, and auditability.