Description

Core Responsibilities

• Provide regular technical guidance and direction to business partners, technical teams, contractors, and vendors.

• Develop secure, high-quality production code and review, debug, and improve code written by others.

• Drive decisions that influence product design, application functionality, technical operations, and engineering processes.

• Serve as a function-wide subject matter expert in one or more technical focus areas.

• Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes.

• Establish consistent validation standards for AI-assisted outputs, including secure coding, peer review, automated testing, correctness, performance, and security review.

• Apply knowledge of the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve automation value.

• Actively contribute to the engineering community as an advocate for firmwide frameworks, tools, and SDLC practices.

• Influence peers and project decision-makers to consider the use and application of leading-edge technologies.

• Support a team culture grounded in diversity, opportunity, inclusion, and respect.

Required Qualifications

• Formal training or certification in software engineering concepts and 5+ years of applied experience.

• Hands-on practical experience delivering system design, application development, testing, and operational stability.

• Advanced Java programming capability.

• Proficiency in automation and continuous delivery methods.

• Proficiency across all aspects of the Software Development Life Cycle.

• Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.

• Demonstrated proficiency in software applications and technical processes within a discipline such as cloud, artificial intelligence, machine learning, or mobile.

• Demonstrated experience leading effective use of approved AI-assisted software development tools for coding, code review, test acceleration, and troubleshooting.

• Ability to set team expectations for validating AI-generated outputs for correctness, performance, and security.

• Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs and outputs, and resiliency and security expectations.

• Experience coaching engineers on safe, compliant adoption of AI-assisted engineering practices within delivery workflows.

• Experience designing, deploying, and managing containerized applications using Kubernetes.

• In-depth knowledge of financial services industry technology systems.

Preferred Qualifications

• Experience with Co-Pilot skills.

• AWS Solution Architect certification.

• Familiarity with Spring Boot.

Operating Environment and Delivery Expectations

• Operate as a senior technical contributor in an agile team focused on enhancing, building, and delivering trusted technology products.

• Apply deep technical expertise and problem-solving methods across multiple technologies and applications.

• Balance delivery speed from AI-assisted engineering with validation standards, security controls, peer review, automated testing, and responsible usage expectations.

• Support production readiness through secure code quality, operational stability, resiliency, CI/CD discipline, and Kubernetes-based application delivery.

• Contribute to broader engineering effectiveness through reusable patterns, firmwide SDLC practices, and adoption of leading-edge technologies

Key Skills

Education

Bachelor's degree