Mastercard

Mastercard

Principal, Product Management GBSC AI Delivery

O'Fallon, Missouri · Principal · Part-time

Sponsorship not specified$156k-$265kDetected 2 days ago
Agentic AIProduct ManagementProduct StrategyStakeholder ManagementCommunication

Stay score

odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level IV · 4×
Level I$65,9781 entry
Level II$89,3982 entries
Level III$112,7983 entries
Level IV$136,2194 entries

This range already reaches Level IV — the maximum four lottery entries.

DOL prevailing wage, 2026-27 wage year · Computer Occupations, All Other (15-1299) · St. Louis, MO-IL. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Green-card intent detected

Mastercard Technologies, LLC obtained a prevailing wage determination for Software Developers in O'FALLON, MISSOURI on 2026-06-18. No matching green-card filing appears in our data yet. The determination expires in 10 days (2026-09-15), and a green-card filing must follow before then or the employer starts over.+1 more active determination on file

Files H-1B transfers

20 transfer filings in the last year, covering 20 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

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About the role

  • Establish product governance, delivery frameworks, and performance metrics to ensure solutions are secure, scalable, measurable, and aligned to enterprise priorities
  • Advanced experience in Product Management focused on enterprise platforms, operational workflows, and business transformation

Responsibilities

  • Partner with business, operations, and technology leaders to identify high-impact opportunities, prioritize investments, and deliver scalable solutions across global teams and markets
  • Drive simplification and standardization across platforms, workflows, and operating models, reducing fragmentation and enabling scalable, reusable capabilities
  • Define and lead the product strategy for enterprise workflows across Finance, HR, Legal, and other global business operations, aligning technology investments to measurable business outcomes
  • Lead the transformation toward autonomous enterprise operations by embedding agentic AI, workflow automation, and intelligent orchestration into critical business processes
  • Ability to lead through ambiguity, influence across functions, and drive alignment on enterprise-wide priorities

Requirements

  • Strong ability to translate complex global business challenges into scalable product strategies, roadmaps, and measurable outcomes using modern tech product management frameworks
  • Strong executive communication and stakeholder management skills, with the ability to influence senior leaders across business and technology organizations

Compensation

  • In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary and may be eligible for an annual bonus or commissions dependi

Benefits

  • Ability to balance long-term product vision with hands-on execution in fast-paced, highly matrixed environments

This listing is sourced directly from Mastercard's careers page and normalized into a canonical job model.