JOB SUMMARY
This role focuses on leveraging Generative AI (GenAI) coding assistants to enhance daily engineering workflows throughout the Software Development Life Cycle (SDLC). Responsibilities include using AI for implementation, refactoring, unit testing, regression support, code reviews, scripting/automation, troubleshooting, and documentation, always applying engineering judgment and validation. The role involves practical familiarity with tools such as GitHub Copilot or Claude Code. Candidates will use AI assistance for common development tasks, taking ownership of correctness and quality, and applying GenAI to reduce context switching and accelerate delivery. It also involves working knowledge of agentic workflows, spec-driven development, and custom instructions and prompt engineering, with the ability to establish team-level practices for effective AI-assisted development.

Key Responsibilities
• Uses AI assistance for common dev tasks (code suggestions, test generation, review support, automation scripts, troubleshooting) with clear ownership for correctness and quality.
• Applies GenAI in ways that reduce context switching and accelerate delivery across typical workflows (not limited to writing new code).
• Demonstrates practical familiarity with GitHub Copilot and/or Claude Code within IDE/CLI-style workflows.
• Working knowledge of agentic workflows, spec-driven development (translating low-level design artifacts such as class structures, API contracts, and data models into structured specs that guide AI-assisted implementation), and custom instructions and prompt engineering, with the ability to establish team-level practices for effective AI-assisted development.

Required Qualifications
• Demonstrated exposure to, or hands-on experience with, GenAI coding assistants used across day-to-day engineering workflows in the SDLC-implementation, refactoring, unit testing, regression support, code reviews, scripting/automation, troubleshooting, and documentation-while applying engineering judgment and validation.
• Practical familiarity with tools such as GitHub Copilot or Claude Code is expected.
• Education: Bachelor's degree in Computer Science, Software Engineering, or related technical field, or equivalent practical experience
• Experience:
o 7+ years of professional software engineering experience in actively developing large scale software using: Java, Spring framework, cloud development, and Web Services supporting high volume transactions in a highly available environment.
o 2+ years of hands-on experience with AI/ML implementation and production deployment
o 6+ years of experience working with containers and microservices in the cloud.
o 6+ years of experience in cloud deployment in a continuous integration, and continuous delivery model (CI/CD).
o 2+ years of experience with Pivotal Cloud Foundry (PCF), or AWS or GCP.
o 2+ years' experience working with databases like MongoDB, Aerospike, and/or PostgreSQL.
o 2+ years Prior experience in IT Transformations and system modernization initiatives from legacy to distributed platforms, i.e., Mainframe Cobol apps/DB2 to Java apps/SQL or MongoDB
o Hands-on experience with Large Language Models (e.g., GPT-5, Claude, Gemini, PaLM)
• Domain Expertise: Understanding of broker-dealer capabilities and operations.
• Communication: Excellent communication skills; proven ability to communicate and lead other engineers in a collaborative environment
• Execution Focus: Collaborative mindset coupled with a bias for action to effectively engage with fellow developers, Architects, and adjacent teams, etc.

Preferred Qualifications
• Master's degree in Information Technology, Computer Science, related degree, OR related practical experience
• Good knowledge of messaging technologies (Rabbit MQ, Kafka, or equivalent)
• Experience in Financial Services industry
• Experience in Test Driven Development, QA Automation and Quality mindset and behaviors
• Proficient in developing Visio diagrams, architectural and design documentations, functional and technical specifications, automated test process
• Willingness to learn all aspects of tech stack and document
• Ability to research and document production and test environments along with architecture and design work
• Knowledge of Agile methodology and experience in an Agile working environment
• Experience with the Atlassian tool stack (JIRA and Confluence)