Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale
Advises cross-functional teams on technological matters within domain of expertise and serves as the function's go-to subject matter expert
Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies
Influences leaders and senior stakeholders across business, product, and technology teams
Engineers the platform's query and data access layer over firmwide code intelligence infrastructure, owning query latency, data freshness, resiliency, and cost characteristics as consumption grows across the firm's codebase
Defines how SDLC controls, compliance checks, and engineering workflows execute against real code structure rather than manual review, and drives adoption by delivering the reference integrations, consumption patterns, and standards other teams build against
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and advanced applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Expert in one or more programming language(s), preferably Java
Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data, grounded in a strong understanding of responsible AI use, control expectations, and risk-based governance in engineering workflows
Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines
Ability to present and effectively communicate with Senior Leaders and Executives
Practical cloud native experience
Demonstrated experience designing and operating platform APIs and data services consumed by other engineering teams, including contract design, versioning, and backward compatibility as the consumer base grows
Hands-on experience building high-volume, data-intensive systems where query latency, data freshness, and index or storage design determine whether the product is usable, including the associated capacity, cost, and resiliency trade-offs
Experience delivering an internal platform as a product, establishing the consumption patterns, reference implementations, and documentation that drive measurable adoption across multiple teams, and evolving that platform without breaking existing consumers
Preferred qualifications, capabilities, and skills
Experience working with structured representations of source code, such as abstract syntax trees, symbol or dependency graphs, or large-scale code search indexes, and exposing them through queryable interfaces
Experience automating SDLC controls, audit evidence collection, or change management and regulatory checks in a controlled or regulated engineering environment
Experience building developer-facing tooling or platforms adopted across a large engineering organization, including supplying trustworthy code context to AI-assisted development tools
