AI Product Manager: Enterprise Platform & Workflows

Doist; Midvale (UT); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Volunteer hours & donations

Employee Resource Groups

Fertility & family planning

Parental leave

Mental health support

Tuition reimbursement

Pet insurance

And more

Job summary

Berkadia is seeking a Product Manager, AI to shape and scale an enterprise AI platform for investment sales, mortgage banking, loan servicing, and corporate workflows. You will partner with data scientists, engineers, and business leaders to translate needs into scalable AI capabilities.

Responsibilities include defining the vision, roadmap, and operating model for the platform, applying SDLC and Agile practices, and driving secure, governable AI integrations across the organization.

Qualifications

• 5+ years of product-management experience delivering software in an enterprise environment.
• 2+ years of experience on AI-specific products or capabilities, such as generative AI or AI agents.
• Hands-on technical experience in software engineering, data, analytics, ML, or related field preferred.
• Experience translating complex business processes for internal enterprise users and CRM/workflow integrations.

Responsibilities

• Define vision, strategy, and roadmap for an enterprise AI platform.
• Synthesize business, technical, user, and operational inputs into clear product decisions.
• Partner with data scientists, ML engineers, software engineers, solution architects, and business stakeholders.
• Drive secure, governed AI integrations across enterprise data and systems.

Skills

Product management

AI-enabled products

Agile methodologies

Stakeholder management

Cross-functional collaboration

SDLC knowledge

Education

Bachelor’s degree or equivalent practical experience

Job description

Berkadia is seeking a Product Manager, AI to shape and scale an enterprise AI platform for investment sales, mortgage banking, loan servicing, and corporate workflows. You will partner with data scientists, engineers, and business leaders to translate needs into scalable AI capabilities.

Responsibilities include defining the vision, roadmap, and operating model for the platform, applying SDLC and Agile practices, and driving secure, governable AI integrations across the organization.