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Salary
≈ $141k – $259k per year (Estimated)
Location
In office (New York)
Seniority
Senior

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Sep 15, 2026.

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Profile match

UBS

Headquartered in Zurich, Switzerland, UBS is a leading global financial services firm and one of the world's largest wealth managers. The company provides a comprehensive range of solutions, including private banking, personal and corporate banking, asset management, and investment banking services. Operating in major financial centers across the globe, the institution assists high-net-worth individuals, corporations, and institutional clients in managing and growing their assets.
Backed by Bluelion
Do you want to play a key role in the front office of an investment bank? Are you passionate about algorithmic trading technology? Do you have experience building real-time, low-latency pricing systems and applying AI to automate workflows, surface insights and deliver robust, scalable Java server-side platforms?

At UBS, we re-imagine the way we work, connect with colleagues, clients and partners, and deliver value. Our quantitative development teams sit within the investment bank business, driving greater responsiveness, adaptability and innovation.

We’re looking for a new teammate with exceptional AI skills to help advance our Equity Derivatives platform. In this role, you will:

  • architect and deliver our new global equity options RFQ, auto-pricing and electronic trading platform
  • work alongside business users to translate complex business and regulatory requirements, manual processes and trading flows into innovative, automated solutions
  • leverage AI to further automate business flows and deliver next-generation analytics and signals into the platform
  • apply a broad range of software engineering practices to ensure the quality, security, reliability and compliance of our solutions, focusing on both functional and non-functional needs
  • work closely with the global team to evolve the platform, build observability into our solutions, monitor production health, resolve incidents and remediate the root causes of risks and issues

• share AI, technical and domain knowledge with the team, mentor colleagues, support hiring and contribute regularly to our engineering culture and internal communities

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