• Lead the implementation of performance practices in large-scale GPU infrastructure, delivering powerful tools, methodologies, and flows to validate and improve multiple datacenter products concurrently. • Align next-generation AI workloads with next-generation datacenter builds for NVIDIA GPUs, CPUs, and networking hardware. • Engage early with HW/FW/SW/platform internal and customer teams. • Develop engineering solutions that provide continuous insights into the performance of AI workloads in evolving environments, generating swift insights into improvements and regressions. • Decompose high-complexity performance or stability issues into minimal reproduction cases, working towards identifying the root cause. • Participate in collaborations with various SW and FW teams (BMC/SBIOS/OS/drivers, etc.) to develop outstanding methods and tools. • Analyze, debug, and resolve critical firmware and software issues to achieve the highest AI workload performance at scale.

• You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery. • You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs. • You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them. • You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts. • You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks. • You will help develop talent on your team by providing feedback and guidance, and leading by example.

• Design and implement task-focused AI agents that assist thousands of professional’s audit work. • Building Document understanding and structured-data extraction systems. • Leading production-grade AI services and shipping working capabilities quickly and iterating with Product & customer teams. • Work across TAA's product portfolio, enabling other teams while building AI solutions that can be applied to multiple products and customer segments. • Design and implement AI features using Python and modern frameworks. • Build intelligent document processing, automated workflows, and AI-powered analytics with a focus on security, product experience, and scalability. • Work in Audit’s collaborative model where engineers understand business problems as deeply as technical solutions, partnering closely with product managers who prototype their own ideas.

• Own growth projects end-to-end: Scope the work, write the frontend and backend, ship to production, and iterate based on what the data says. • Build in-product growth features: Ship the onboarding, activation, retention, and expansion surfaces that turn signups into paying customers. • Improve the playground: Our highest-leverage conversion surface. Make it faster, smarter, and easier for a developer to go from "trying it" to "using it." • Ship conversion landing pages: Own the pages closest to conversion: partner integrations, competitive comparisons, use cases, campaign pages. • Build internal tooling: Ship the UIs the Product Growth team uses to operate. • Run experiments and measure: Instrument what you build. Run real A/B tests. • Improve developer experience where it touches growth: SDK ergonomics, sample code, starter templates, first-run experiences.