AI-Enabled Java Tech Lead for Financial Platform

Relha LLC; Princeton, Northern (NJ, KY); Hybrid; USD 142,000 - 215,000; Full time

Job summary

S&P Global Dow Jones Indices is seeking a Software Engineering Technical Team Lead to drive the design and delivery of an AI‑assisted index calculation and backtesting platform. You will lead Java full‑stack engineering, cloud integration with AWS, and oversee analytics workflows in a hands‑on leadership role.

The role emphasizes mentoring, architecture reviews, production readiness, and collaboration with product, QA, and data teams to ensure scalable, auditable platform components.

Qualifications

• 12+ years of software engineering experience, with Java full‑stack and enterprise platform delivery.
• 5+ years of technical leadership, mentoring engineers and guiding delivery teams.
• Strong hands‑on experience with Java, Spring Boot, REST APIs, microservices, relational databases, backend service design.

Responsibilities

• Lead engineering delivery of an AI‑enabled financial platform for index calculation and backtesting.
• Define architecture, standards, testing expectations, and delivery patterns for the team.
• Mentor engineers, review architecture and code, and collaborate with stakeholders to translate requirements into plans.

Skills

Java

Full-stack development

Cloud AWS

Technical leadership

Architectural design

Code reviews

AI-assisted development

Financial platforms understanding

Testing and CI/CD

Tools

Spring Boot

REST APIs

Microservices

JPA/Hibernate

Maven/Gradle

AWS services (Step Functions, Lambda)

Data platforms (Databricks, Snowflake)

Job description

S&P Global Dow Jones Indices is seeking a Software Engineering Technical Team Lead to drive the design and delivery of an AI‑assisted index calculation and backtesting platform. You will lead Java full‑stack engineering, cloud integration with AWS, and oversee analytics workflows in a hands‑on leadership role.

The role emphasizes mentoring, architecture reviews, production readiness, and collaboration with product, QA, and data teams to ensure scalable, auditable platform components.