Lead Agentic AI Designer

Mastercard

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Purchase, NY
Salary
$150,000–$254,000 / yr
Posted
5 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $220k
This role $202k
$137k most similar roles pay here $276k

This role pays less than 66% of similar roles. Most pay $184,900–$254,750 — the shaded band above. At the midpoint, this role pays about $202k versus about $220k for comparable roles.

Based on 239 similar postings.

Employer

About Mastercard

Mastercard is a global technology company in the payments industry, processing transactions between financial institutions and merchants using its extensive network of credit, debit, and prepaid card products. Industry: Payments Technology & Financial Services

Mastercard currently has 116 open roles on FindRole.

Listed pay typically runs $122,000–$207,000 across 104 roles with salary data.

Most-posted roles

View all roles at Mastercard

At a glance

TL;DR · Lead Agentic AI Designer

The Lead Agentic AI Designer joins the Operational Intelligence team to design, build, and scale enterprise-grade, multi-agent AI platforms. This role focuses on developing LLM-powered applications and autonomous systems that power critical operational workflows, including reconciliation processes, transaction insights, anomaly detection, and operational AI copilots. The successful candidate will architect agent workflows featuring memory strategies, tool integration, guardrails, and human-in-the-loop patterns while implementing retrieval-augmented generation and context engineering using tools like Mem0 and Redis. Key responsibilities include integrating systems with enterprise data platforms, ensuring production readiness through observability and evaluation, and mentoring other engineers. The role requires expertise in Python, APIs, distributed systems, and cloud-native platforms to solve complex problems within the payment and operational domain, moving solutions from initial proof of concept through to full production deployment.

What you'll do

  • Design, build, and deploy LLM-powered applications and multi-agent systems for enterprise workflows.
  • Architect agent workflows including memory strategies, tool integration, guardrails, and human-in-the-loop patterns.
  • Implement retrieval-augmented generation (RAG) and context engineering using tools like Mem0 and Redis.
  • Integrate agentic systems with internal enterprise data platforms and payment processing workflows.
  • Develop scalable backend services using Python, APIs, and distributed system patterns.
  • Drive observability, evaluation, and reliability metrics to ensure production-ready AI performance.
  • Partner with product teams to move solutions from proof of concept to MVP and production.
  • Mentor engineers and establish technical standards for agentic AI development across the team.

What we're looking for

  • Strong experience building AI/ML or backend systems using modern engineering practices.
  • Hands-on experience developing LLM-powered applications, RAG pipelines, and agent-based systems.
  • Proven experience delivering production-scale services in distributed environments.
  • Strong proficiency in Python, APIs, and distributed systems design.
  • Ability to independently own complex technical problems and drive them to production.
  • Experience with agentic AI systems and autonomous workflows (preferred).
  • Exposure to fintech, payments, or regulated environments (preferred).
  • Experience with vector or graph databases and cloud deployment (preferred).

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