Senior AI Engineer – Wealth & Investment Analytics

BNY

New York (NY)

On-site

USD 180,000 - 250,000

Full time

2 days ago
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Benefits offered by this job

Competitive compensation
Paid time off and volunteer leave
401(k)

Job summary

BNY is seeking a senior AI/Software Engineer to build and scale AI-powered Wealth & Investment Management solutions. You will work at the intersection of investment expertise, quantitative analysis, and modern AI technologies to deliver intelligent applications that enhance portfolio construction, research, and client outcomes.

The role requires strong math, analytical skills, and practical experience with data pipelines, APIs, and scalable analytics.

Qualifications

  • Strong software engineering and quantitative analytics foundation.
  • Proficient in Python and data analysis libraries.
  • Experience with financial data sets and market data vendors.
  • Familiarity with cloud-native development, APIs, databases, and SDLC.
  • Exposure to Generative AI, ML, and retrieval-augmented generation (RAG).
  • Hands-on experience building data pipelines and scalable analytical apps.

Responsibilities

  • Design and develop AI-powered applications for Wealth & Investment Management.
  • Build portfolio analytics, research, and decision-support solutions.
  • Integrate data from multiple investment platforms and data sources.
  • Develop data pipelines, APIs, and reusable software components.
  • Apply quantitative techniques for portfolio construction, risk analysis, and insights.
  • Contribute to frameworks, standards, and documentation across AI initiatives.

Skills

Python
Data analysis
APIs
Data pipelines
Generative AI
RAG
Cloud-native
Communication
Team collaboration
Software design

Tools

FactSet
Bloomberg
Morningstar

Job description

BNY is seeking a senior AI/Software Engineer to build and scale AI-powered Wealth & Investment Management solutions. You will work at the intersection of investment expertise, quantitative analysis, and modern AI technologies to deliver intelligent applications that enhance portfolio construction, research, and client outcomes.

The role requires strong math, analytical skills, and practical experience with data pipelines, APIs, and scalable analytics.

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