Neara - Lead Engineer, Engineering Productivity

• Lead the architecture and evolution of our inner and outer developer loop—covering build orchestration, dependency management, and large monorepo workflows—to support rapid iteration at scale and the improvement of developer productivity. • Evolve our software engineering practices to leverage AI-enabled productivity—forging the way forward with tools and techniques and bringing the team along with you. • Create a measurement-driven culture to diagnose and resolve complex and ambiguous challenges across core infrastructure and developer tooling, using deep systems expertise and low-level profiling, tracing, and debugging techniques. • Lead cross-team, cross-organization initiatives to reduce friction in the development lifecycle and address systemic risks, and enable teams to scale safely and efficiently. • Partner closely with product management, engineering leadership, and senior stakeholders to define long-term technical strategy for engineering productivity. • Lead and mentor engineers to grow domain expertise, empowering the broader engineering organization to collaborate effectively and deliver on these initiatives. • Proven track record of building and operating large-scale, production-grade systems, with deep expertise in systems programming, infrastructure platforms, or developer tooling. • Proven track record of leading complex, high-impact technical initiatives that span multiple teams and materially improve developer productivity. • Experience designing infrastructure or internal platforms as products, with strong empathy for developer workflows and usability. • Deep understanding of modern build system architectures (such as Bazel, Gradle, Cargo, etc) with experience in areas such as dependency modelling, incremental builds, caching and remote execution. • Strong communication and collaboration skills, with the ability to influence technical direction and align stakeholders without direct authority. • Demonstrated ability to operate effectively in ambiguous problem spaces and make sound architectural decisions with incomplete information. • Continuous learner with a passion for improving engineering effectiveness at scale.