As a Software Engineer at Meta, my current focus is on adopting new hardware platforms across Meta to unlock the next wave of AGI (Artificial General Intelligence). I work at the intersection of distributed systems, AI infrastructure, and hardware enablement by designing reliable, scalable platforms that allow intelligent services and AI-driven workflows to operate safely in real-world production environments.

At Meta, I’ve led initiatives to integrate cutting-edge hardware into our datacenter fleet, optimizing compute utilization and enabling large-scale AI workloads. My work spans capacity management, autoscaling, and reliability engineering ensuring that new hardware is seamlessly adopted, delivers measurable performance gains, and maintains strict reliability guarantees.

I collaborate closely with cross-functional teams to build the systems and tooling that support AGI research and deployment. This includes developing infrastructure for agentic AI systems, safety guardrails for autonomous decision-making, and evaluation frameworks for real-world AI deployment.

Areas I focus on:
• Hardware adoption and enablement for AGI-scale workloads
• Distributed systems powering large-scale AI and agentic workflows
• Reliability and safety for autonomous systems
• Datacenter-scale resource scheduling and optimization
• Developer tooling and automation (including AI-assisted workflows)
• Open source tooling and contribution workflows

Topics I frequently write and speak about:
• Infrastructure for AGI and intelligent systems
• Hardware/software co-design for AI workloads
• Reliability challenges in AI-driven systems
• Scaling and optimizing compute for next-generation AI

If you’re working on infrastructure for AGI, hardware adoption, or scaling intelligent systems, I’d love to connect and share ideas.