Engineering Lead for AI-Driven Fixed Income Systems

S&P Global; Princeton (NJ); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health care coverage

Flexible downtime

Continuous learning resources

Competitive pay

Retirement planning

Continuing education program

Company-matched student loan contrib.

Financial wellness programs

Family friendly perks

Retail discounts

Referral incentive awards

Job summary

S&P Global in Princeton, NJ seeks an engineering leader to design and develop high‑performance calculation engines and services for fixed income indices. You will mentor a team of engineers while integrating AI‑driven solutions to boost data processing, reliability and system scalability in a cloud‑native environment.

The role requires 10+ years of enterprise Java experience, deep Spring and AWS expertise, and a proven ability to deploy AI/ML models into enterprise platforms.

Qualifications

• Requires 10+ years of enterprise Java development with Spring, AWS, and distributed systems.
• Proven design experience in fixed income systems and deploying AI/ML models into enterprise platforms.
• Mentor a team and lead design/development of high-performance calculation engines.

Responsibilities

• Lead design and development of high-performance calculation engines and services for fixed income indices.
• Mentor a team of engineers and guide technical decision-making.
• Integrate AI-driven solutions to enhance data processing and system scalability.

Skills

Java 17/21

Spring Boot

Microservices

Kafka

AWS

SQL

NoSQL

AI/ML Integration

Fixed Income Analytics

System Design

Agile Methodologies

JVM Tuning

RESTful API

Kotlin

Scala

Distributed Systems

Tools

Kafka

SQL

NoSQL

JVM Tuning

Job description

S&P Global in Princeton, NJ seeks an engineering leader to design and develop high‑performance calculation engines and services for fixed income indices. You will mentor a team of engineers while integrating AI‑driven solutions to boost data processing, reliability and system scalability in a cloud‑native environment.

The role requires 10+ years of enterprise Java experience, deep Spring and AWS expertise, and a proven ability to deploy AI/ML models into enterprise platforms.