I’m Arkaan Quanunga, a software engineer at Roku building production AI agents across codebases, developer tools and physical devices. My work covers multi-agent orchestration, persistent state and memory, MCP tool interfaces, retrieval, isolated execution and validation. Explore QAntum, Explorer and Forge, alongside my earlier AWS and video infrastructure work at V-Nova.
Ownership: ~4,000 commits and ~70% of Explorer version-control history, across a 17-engineer contributor base.
The Roku stack — Explorer, QAntum, and Forge — is a patent-pending invention for turning manual QA into a data-driven process that finds functional and visual defects on devices with less manual oversight.
Read it on the career timelineWritten with NVIDIA engineers at V-Nova. The article covers VC6 codec performance and a GPU-accelerated transcoding pipeline, published on NVIDIA’s developer blog.
Read the NVIDIA articleSlack-Native Multi-Agent QA Orchestrator
A Slack-native multi-agent QA orchestration platform routing engineering and QA requests across specialized agents via an extensible capability protocol. Features shared and user memory, Model Context Protocol (MCP) integrations, and autonomous MR/PR generation and validation flows—backed by production usage across ~100 engineers.
Autonomous Exploratory Testing Platform
A production autonomous QA platform for firmware and Grand Central product areas. Combines PPO/LSTM reinforcement learning, ChromaDB multimodal RAG, dual validators, and MCP-based device control to navigate device UIs, surface potential issues, and flag visual regressions with minimal human oversight.
AI Test-Authoring & Automation Agent
An intelligent AI automation agent that investigates product-area workstreams, creates detailed automation tickets, and autonomously generates, validates, and runs regression test suites across repositories using isolated git worktrees.
Distributed Video Compression Infrastructure
High-throughput distributed cloud infrastructure built on AWS with Terraform, collaborating with Meta, Intel, and SPIE to automate video compression quality evaluation across thousands of parallel transcoding jobs.
At Roku, I develop and deploy the next evolution of quality engineering: agent systems that autonomously navigate physical device interfaces, author robust regression tests, and orchestrate across complex developer tools. This unified stack connects code changes directly to risk-based automated physical device exploration.
Proven across production multi-agent systems, large-scale video transcoding cloud infrastructure, and real-time computer vision hardware.
PPO and LSTM reinforcement learning policies combined with multimodal vision models and ChromaDB vector retrieval to navigate state spaces autonomously.
Capability routing protocols, Model Context Protocol (MCP) integrations, isolated agent memory, and automated code review Remediator loops.
Scalable AWS infrastructure automated with Terraform, FFmpeg pipelines, GPU transcoding acceleration (NVIDIA DevBlog), and VMAF perceptual quality benchmarking.
Real-time object detection (YOLO26), MediaPipe hand gesture tracking, monocle optical pipelines, and spatial glass HUD compositors.
Contact me about AI engineering, agent infrastructure or technical collaborations.