• Lead the team responsible for building and scaling Stake's payments capabilities • Collaborate with Product, Operations, Finance, Risk and Compliance • Define how customers fund, move and access their money across Stake • Shape technical, operational and cultural foundations that support Stake's next growth phase • Improve reliability, scalability and operational resilience of Stake's payments platform • Build trusted partnerships across various teams and contribute to broader engineering strategy

• Design and build agentic LLM pipelines that power AI features across the product. • Build full-stack product features: Python/FastAPI web applications, TypeScript/React web tooling. • Prompt-engineer and iterate on LLM prompts and models. Evaluate and recommend improvements based on accuracy, latency, and cost. • Strengthen our evaluation framework: curated datasets, evals, experiments, and regression identification, so we can ship changes with confidence. • Improve production observability: accuracy signals and feedback loops. • Contribute to architecture and technical direction. • Actively partner with other product teams to understand their AI use cases and identify how to best enable and support them. • Advise on when to apply an AI/LLM solution, and when not to: championing AI where it drives speed and ROI and steering away where it doesn't.

• Reimagine and implement the future of tech for the music industry • Work as part of a dynamic and highly effective team • Own the creation and delivery of highly innovative products • Implement maintainable solutions with high quality and reliability that can scale as our business continues to grow and expand • Learn and grow as a professional through close collaboration with your team members and engineering leaders, and by being part of culture of continuous improvement and learning • Provide mentorship to other engineers, fostering their professional growth and success • Respond to incidents and perform on-call duties with an eye towards root cause fixes and improvements

• Design and build software code and cloud services for Data Management, including providing a catalog, managing metadata and life cycle of datasets and checkpoints • Connect with other technical leaders across NVIDIA to ensure you are using existing technologies where possible and that we are collaborating appropriately with their systems • Collaborate with the NVIDIA research team to utilize new storage and compute innovations, including GPU direct storage and DPU