AI-Driven QIS Platform Engineer

UBS

New York (NY)

On-site

USD 145,000 - 172,500

Full time

14 days+

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Job summary

UBS's QIS Platform team seeks a highly skilled Python engineer to own production analytics, automated checks and AI-driven improvements in a front-office adjacent setting in New York.

You will design scalable data pipelines, contribute to AI initiatives, collaborate with quants and data scientists, and drive durable platform enhancements across monitoring, observability, and automation in a fast-paced environment.

Qualifications

  • Production-grade Python solutions experience.
  • Hands-on AI/ML in production or advanced prototyping.
  • Experience with data platforms, cloud or distributed systems.
  • Strong data analysis and problem-solving in fast-paced environments.
  • End-to-end ownership mindset across tech and business domains.
  • Experience building monitoring, observability or automation frameworks.
  • Familiarity with systematic strategies in finance or front-office platforms.
  • Track record of moving solutions from prototype to production or mentoring others.
  • Curiosity for applying AI to improve workflows with ethical risk awareness.

Responsibilities

  • Design, develop, and maintain production-grade Python code for QIS platform analytics, controls, monitoring and workflow automation.
  • Build scalable data pipelines and validation frameworks used in live environments.
  • Lead AI/ML initiatives across the QIS platform, including monitoring and automation of controls.
  • Collaborate with quants and data scientists to industrialize AI concepts into production.
  • Design automated checks, dashboards, and observability frameworks.
  • Investigate data or production anomalies and drive cross-team resolution.

Skills

Python production
AI ML production
Data platforms
Cloud computing
Observability

Tools

Cloud platforms
Distributed systems
Monitoring tooling

Job description

UBS's QIS Platform team seeks a highly skilled Python engineer to own production analytics, automated checks and AI-driven improvements in a front-office adjacent setting in New York.

You will design scalable data pipelines, contribute to AI initiatives, collaborate with quants and data scientists, and drive durable platform enhancements across monitoring, observability, and automation in a fast-paced environment.

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