Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Strong hands-on experience in Java backend development and Spring Boot in production environments
Proven ability in system design for scalable, secure services using microservices and API-driven architectures
Strong engineering fundamentals including object-oriented programming, design patterns, concurrency, debugging, and performance tuning
Solid testing discipline encompassing unit and integration testing, automation, and code quality practices
Advanced proficiency in programming languages (Java, Python, C#, etc.), Hands-on work with Large Language Models (LLMs) and generative AI.
Experience with distributed systems and cloud platforms (AWS, GCP, Azure).
Expertise in microservices, RESTful APIs, and database technologies (relational/NoSQL) and experience with development and testing tools and frameworks (JUnit, UDF, Tophat, Cucumber, Groovy, Postman, REST Assured, Eclipse, Maven, Jenkins, IntelliJ).
Experience with performance testing tools (JMeter, Blazemeter) and Chaos Monkey Testing.
Preferred qualifications, capabilities, and skills
Cloud certification (AWS, GCP, Azure).
Practical public cloud development experience.
In-depth knowledge of the financial services industry and their IT systems.
Wealth Planning tool experience
Effective communication across teams and management, with a proactive approach to process improvement.
Strong system design, application development, and operational stability skills.
Familiarity with AI/ML frameworks (PyTorch, scikit-learn, Hugging Face).
