Job Positing TitlePrincipal Technical Lead – AI & Platform

About the RoleClientLink is a mission-critical wealth management platform that supports portfolio accounting, investment operations, and client servicing across the enterprise. As part of our strategic modernization journey, we are transforming the platform using up-to-date architecture, event-driven integration, cloud-native technologies, and an enterprise AI Engineering Platform that accelerates software delivery through reusable AI capabilities, standardized engineering workflows, and governance.

We are seeking an experienced Principal Technical Lead – AI & Platform Modernization to lead this transformation. This role combines deep technical expertise, people leadership, software architecture, and AI-enabled engineering to deliver the next generation of ClientLink.

As the senior technical leader, you will define the technical vision, lead an engineering team, establish engineering standards, and drive the adoption of AI-enabled software engineering practices that improve delivery velocity, software quality, and developer productivity.

Key Responsibilities

Technical Strategy & Platform Modernization

- Define and execute the technical strategy for the modernization of the ClientLink platform.
- Lead the transformation of legacy applications into modern, scalable, resilient, and maintainable solutions.




- Establish architecture principles, engineering standards, and modernization roadmaps aligned with enterprise technology strategies.
- Drive the adoption of API-first, event-driven, and cloud-native architectural patterns.
- Balance innovation with operational stability by reducing technical debt while delivering business value.
- Evaluate emerging technologies and recommend strategic investments that strengthen the platform and improve engineering effectiveness.

AI Engineering Platform Leadership

- Lead the evolution and adoption of the enterprise AI Engineering Platform to modernize the software development lifecycle.
- Drive the use of AI-enabled capabilities across requirements analysis, solution architecture, software design, code generation, testing, documentation, and platform modernization.
- Define reusable AI capabilities, including domain-specific skills, plugins, workflows, prompts, and engineering guardrails that enable secure, consistent, and high-quality software delivery.
- Establish governance and best practices for responsible AI adoption, ensuring compliance with enterprise security, risk management, and software engineering standards.
- Champion AI-enabled developer productivity while maintaining human oversight, technical accountability, and engineering excellence.

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