Mentor engineers and contribute reusable patterns and tooling back to the group
Build and improve automation and AI-based tooling that raises engineering leverage across the team
Use enterprise-authorized AI coding-assist tools (code generation and refactoring, test creation, documentation) to improve quality, speed and productivity, validating outputs through peer review, automated testing and secure coding standards
Work with engineering and product teams to deliver platform capabilities that support global investment operations at scale
Required qualifications, capabilities, and skill
Formal training or certification in software engineering concepts and advanced applied experience
Strong hands-on experience with Java and Spring Boot (Java 17 or later), designing, developing, testing, debugging and maintaining production services in a large enterprise environment
Experience distributing and consuming data using event and Kafka streaming, APIs (GraphQL and REST) and bulk methods and experience with relational (SQL) databases and at least one NoSQL store
Hands-on experience in system design, application development, testing and operational stability, including production support
Solid understanding of the Software Development Life Cycle, agile delivery, CI/CD, application resiliency and security with hands-on experience with enterprise-authorized AI-assisted development tools, and the ability to critically evaluate, validate and refine AI-generated output for correctness, performance and security
Understanding of responsible AI use in engineering workflows (data sensitivity, secure handling of inputs and outputs, resiliency and security expectations), and the ability to guide peers on safe and effective use
Preferred qualifications, capabilities, and skills
Knowledge of data mesh distribution patterns using Snowflake and Starburst [CONFIRM: keep as preferred]
Experience building on AWS services (compute, storage, messaging and access management), and experience with infrastructure as code such as Terraform
Experience with a rules engine (for example Drools), Spring Batch, Liquibase and Cucumber (BDD)
Knowledge of financial instrument reference data (identifiers such as ISIN, CUSIP and SEDOL, asset classes, security master concepts)
Knowledge of Python
Interest or experience in AI, agentic tooling or developer-automation platforms
