Senior Software Engineer & Tech Lead · L5
Nov 2026 — PresentGoogle · Sunnyvale, CA
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Tech Lead — TI-VM
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Tech Lead — Borglet Infrastructure
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Tech Lead — Borg Runtime
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Tech Lead — gRuntime
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Tech Lead (Node) — AI/ML Infrastructure
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Architecting planet-scale systems at the intersection of virtualization and AI.
- Currently
- Senior Software Engineer & Tech Lead, Google
- Based in
- Sunnyvale, CA
I build the high-performance, secure infrastructure that powers Google’s most critical workloads, including Gemini, Google DeepMind, and Waymo.
Impact
- Cost savings
- ~$30M+
- ML compute fungibility & fleet virtualization
- SWE-years saved
- 102+
- Equivalent engineering capacity unlocked
- Engineers led
- 11
- Borg Isolation across a multi-million node fleet
About
I engineer the foundational infrastructure that powers the modern AI era. As a Tech Lead at Google, I specialize in designing planet-scale systems where uncompromising security meets extreme performance. My work directly enables the reliable, high-speed execution of Google’s most critical workloads, including Gemini, Google DeepMind, and Waymo.
My expertise lies at the bleeding edge of virtualization, systems programming, and high-performance computing. Whether I'm architecting next-generation C++ node runtimes that deliver over 102+ SWE-years (~$30M+ in cost savings), directing fleet-wide isolation initiatives across millions of nodes, or crafting patent-pending compiler extensions for 3D deep learning hardware, I thrive on translating highly ambiguous architectural challenges into robust, scalable realities.
I don't just write code; I build resilient engines for scale. Armed with deep expertise in modern C++, distributed systems, and low-level hardware-software co-design, my drive is to push the boundaries of what's possible with today’s hardware to unlock tomorrow's technological leaps.
Experience
Software Engineer III & Tech Lead · L4
Nov 2025 — Nov 2026Google · Sunnyvale, CA
Leading node-level runtime architecture across AI/ML Infrastructure and fleet-wide virtualization frameworks.
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Tech Lead — Borg Isolation Commitment
Directing a team of 11 engineers to fortify ecosystem security by transparently converting untrusted jobs to execute inside isolated VMs across a multi-million node global fleet, rigorously balancing security with system efficiency.
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Tech Lead — TI-VM Next-Gen Runtime
Architecting and optimizing the future of virtualized execution environments across the fleet to maximize hardware utilization with minimal performance and memory overhead.
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Tech Lead (Node) — AI/ML Infrastructure
Leading node-level runtime architecture for a confidential initiative supporting Google's rapid AI growth, driving cross-functional alignment across Kernel, Networking, and Fleet Management to scale heterogeneous infrastructure.
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NVMe-Based VM Hotplugging
Spearheaded the architecture and end-to-end implementation of NVMe-based VM hotplugging to plug and unplug NVMe devices without passthrough systems or in-VM dependencies—delivering native host-level filesystem speed and resolving critical I/O bottlenecks for Google DeepMind’s multiprocessing training workloads.
Software Engineer II · L3
Aug 2024 — Nov 2025Google · Sunnyvale, CA
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ML Compute Fungibility & Fleet Virtualization Optimization
Identified and architected next-generation C++ node runtime and virtualization optimizations enabling seamless ML compute fungibility (CPU/GPU/TPU) to maximize global fleet capacity—driving cumulative infrastructure and engineering cost savings equivalent to 102+ SWE-years (~$30M+ in cost savings) and unlocking scale for Gemini.
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Distributed VM Resource Management Parity
Led the architectural design and C++ implementation of a distributed resource management initiative, enabling seamless telemetry extraction and in-place VM updates to execute complex, untrusted multi-tenant ML workloads at planetary scale.
Internships
Software Engineering Intern
May 2023 — Aug 2023
Engineered a high-throughput, multithread-safe C++ API in Borglet for task lifecycle management utilizing lock-free programming to minimize contention. Designed and deployed a novel hierarchical dependency-sharing architecture for modularizing fleet-wide autonomous services within the Borg cluster manager.
Intel Corporation
Software Engineer Intern
Sept 2022 — Apr 2023
Authored a patent-pending C++ compiler extension (pub. #20230237014) for a proprietary IR to support 3D deep learning graphs, unlocking full on-chip hardware acceleration. Boosted ML model inference throughput by 11% via graph-level operator fusion, memory layout transformations, and INT8 mixed-precision optimizations.
Software Developer Intern
May 2022 — Aug 2022
Architected a scalable ML experimentation pipeline on GCP and deployed a highly optimized C++/Go ensembling library that boosted a production NLP API’s F1 score by 4.28% and reduced annotation errors by 50%.
STEP Intern
May 2021 — Aug 2021
Enhanced C++ infrastructure connecting to SpannerDB to capture ML anomaly detection scores, resulting in an 8% increase in bad-actor suspensions and a 10% reduction in scan quota.
Selected work
Proprietary IR & Hardware Acceleration
3D Deep Learning Compiler Extension
Co-invented and authored a C++ compiler extension for a proprietary intermediate representation (IR) supporting 3D deep learning tensor graphs, unlocking full on-chip hardware acceleration and boosting inference throughput by 11%.
Multithreaded Spatial Engine & Pathfinding
OpenStreetMaps Concurrent GIS
Achieved a >56% runtime speedup in a custom C++ Geographic Information System by architecting a concurrent thread-pool engine to parallelize map parsing and pathfinding heuristics, securing a Top-6 placement for route quality.
Adversarial Multi-Agent Reinforcement Learning
NEPIADA Autonomous Drone Swarms
Designed novel multi-agent Reinforcement Learning algorithms (DQN, PPO) that outperformed state-of-the-art methods by converging to a Nash equilibrium in adversarial, partial-information environments simulating drone swarm behavior.
Zero-Allocation Game Tree Search in C
Tournament Reversi AI Engine
Developed a Top-5% ranked Reversi AI engine in C. Implemented an aggressively optimized Minimax search featuring alpha-beta pruning, Zobrist transposition tables (memoization), and killer heuristic move ordering under tight latency constraints.
Stack
Languages
- Modern C++ (17/20/23)
- C
- Go
- Python
- SQL
- Bash
Infrastructure & Hardware
- Borg
- NVMe
- SmartNICs
- Kubernetes
- gRPC & Protocol Buffers
- Spanner & BigQuery
- GCP & AWS
- Docker
- Bazel & CMake
Performance & Profiling
- Perf
- GDB
- Valgrind
- Google Test (gtest)
- PyTest
- CI/CD Pipelines
AI / ML & Core Domains
- Systems Design
- Lock-Free Programming
- Compiler Optimization
- Distributed Systems
- High-Performance Networking
- PyTorch & TensorFlow
- Model Pruning / INT8
- RLlib
Education
University of Toronto
Bachelor of Applied Science in Computer Engineering
Sept 2019 — Apr 2024
- High Honours (87.5%+ Cumulative Average)
- Certificate in Artificial Intelligence
- Minor in Engineering Business
Contact
The best way to reach me is by email.