Develop well-designed, testable, efficient, and maintainable code to solve business and technology problems.
Participate in solution design, code reviews, technical documentation, testing, release planning, deployment activities, and production readiness.
Support application quality through automated testing, software verification, debugging, performance tuning, and secure coding practices.
Troubleshoot, debug, upgrade, and enhance existing systems while managing technical debt and improving software maintainability.
Ensure software solutions are aligned to enterprise architecture, security, privacy, resiliency, observability, and change management standards.
Leverage existing products, reusable components, and platform capabilities to improve engineering efficiency and avoid duplication.
Collaborate across product, engineering, data science, platform, operations, risk, and governance teams to deliver high-quality AI-enabled capabilities.
To be successful in this role, we’re seeking the following
Preferred 7+ years of experience in software development, full stack engineering, application development, platform support, or related technology roles.
Experience developing, supporting, and enhancing enterprise applications using modern application, API, integration, and platform technologies.
Strong understanding of software development lifecycle practices, Agile delivery, CI/CD, automated testing, code reviews, release management, and production support.
Experience building secure, scalable, testable, and maintainable software in complex enterprise environments.
Familiarity with AI-enabled applications, automation platforms, data-driven products, model integrations, prompt-based workflows, or AI/ML-enabled software solutions.
Strong troubleshooting skills, including debugging application behavior, reviewing logs, resolving defects, and improving application reliability.
Understanding of security, privacy, performance, resiliency, and maintainability considerations in enterprise software development.
Ability to work effectively with product, engineering, data science, platform, operations, risk, and governance teams.
Strong communication, problem-solving, ownership, and collaboration skills.
Bachelor’s degree in computer science, Engineering, or a related discipline, or equivalent work experience required.
Experience in financial services, enterprise technology, or another highly regulated environment.
Exposure to generative AI, large language models, retrieval systems, agentic workflows, AI-assisted development, or enterprise AI platforms.
Experience with cloud platforms, containerization, microservices, DevOps tooling, observability, APIs, data integrations, and production support practices.
Experience with Python, Java, JavaScript / TypeScript, React, Node.js, SQL / NoSQL databases, APIs, and modern engineering toolchains.
Familiarity with AI observability, workflow automation, prompt orchestration, model lifecycle tooling, or data pipeline integration is a plus.
