BPM & AI Workflow Project Manager

Capgemini

New York (NY)

On-site

USD 86,000 - 127,000

Full time

5 days ago
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Benefits offered by this job

Paid time off
Medical, dental, and vision coverage
Retirement savings plans (e.g., 401(k)
Employee assistance programs
Other local benefits

Job summary

Capgemini is seeking a Technical Project Manager in Jersey City, NJ to lead complex workflow and automation initiatives. You will partner with operations, product, technology, data and risk teams to define current and target workflows, case routing, approvals, and escalation paths.

Responsibilities include translating requirements for ServiceNow, Pega or Appian, driving backlog with epics and user stories, and aligning delivery across platforms and data sources.

Qualifications

  • 8+ years in technology project/program management or related roles.
  • Experience with workflow/case-management platforms (ServiceNow, Pega, Appian).
  • Ability to map complex processes into clear requirements and user stories.

Responsibilities

  • Partner with stakeholders to define workflows, rules, SLAs and escalations.
  • Translate requirements into functional specs for BPM platforms.
  • Drive backlog with epics, features, and user stories in collaboration with delivery teams.
  • Coordinate cross-system design across APIs and data sources for straight-through processing.
  • Identify AI/Data opportunities for classification, routing and decision support.

Skills

Project management
Stakeholder management
Agile delivery
Workflow/case management
Data & AI awareness

Education

Bachelor/equivalent in a related field

Tools

ServiceNow
Pega
Appian

Job description

Capgemini is seeking a Technical Project Manager in Jersey City, NJ to lead complex workflow and automation initiatives. You will partner with operations, product, technology, data and risk teams to define current and target workflows, case routing, approvals, and escalation paths.

Responsibilities include translating requirements for ServiceNow, Pega or Appian, driving backlog with epics and user stories, and aligning delivery across platforms and data sources.

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