Isak Karlsson — Software Engineer

Summary

A builder, first and foremost. I start from the problem and the people it serves, keep the goal in view, and reach for the right tool for each job rather than forcing a favorite — adapting as the work demands. That instinct sits on top of 7+ years of industry experience across AWS and Raytheon, 15+ years of self-directed programming and design, and formal training in computer science and mathematics at UC Berkeley. Work spans systems and distributed-systems engineering, systems integration, and applied machine learning and reinforcement learning. Previously held a DoD Secret clearance (2018–2023).

Experience

Software Development Engineer II · Amazon Web Services (AWS) Jan 2026 – present

Building an LLM-based autonomous institutional-knowledge agent that recovers knowledge lost to employee churn and turnover. It crawls internal infrastructure, pipelines, ETLs, code bases, and documentation systems (wiki, Quip, SharePoint) and aggregates them into a curated, continuously maintained knowledge base.
Designed the self-healing curation system: event- and schedule-driven automation prunes, cleans, merges, and expands the knowledge base as new events arrive, with a "curator" filtering inputs and several learning systems maintaining accuracy.

System Development Engineer II · Amazon Web Services (AWS) Oct 2022 – Feb 2026

Built infrastructure and systems for supply-chain planning.
Worked across application security and large-scale distributed systems.
In the role's final year, initiated the LLM-based institutional-knowledge agent described above — now continuing in the current role.

Systems Engineer · Raytheon Missiles & Defense Sep 2018 – Oct 2022

Lead engineer across AI/ML efforts: object detection and classification in SAR and IR imagery, edge-processor development and integration (NVIDIA Tegra), reinforcement learning for large-scale swarm autonomy, and learning-to-optimize for combinatorial problems in distributed systems. Instructor for Raytheon's Advanced Technical Education Program (reinforcement learning).

Research Assistant · Dr. Peter Cheeseman, Berkeley, CA 2015 – 2017

Teaching Assistant · University of California, Berkeley 2016

Selected Work & Research

Institutional-Knowledge Agent 2025 – present

LLM-based autonomous agent that recovers knowledge lost to employee churn — crawling internal infrastructure, pipelines, ETLs, code bases, and documentation (wiki, Quip, SharePoint) into a curated, continuously maintained knowledge base.

Self-Healing Knowledge Curation 2025 – present

Event- and schedule-driven system that prunes, cleans, merges, and expands the knowledge base as new events arrive; a "curator" filters inputs while several learning systems maintain accuracy.

Edge Computing 2020 – 2022

Development and integration on modern edge processors (NVIDIA Tegra); research on non-Von-Neumann architectures for edge processing.

Reinforcement Learning 2019 – 2022

Instructor for Raytheon's Advanced Technical Education Program; OpenAI Gym environment lead developer and agent researcher.

Image Classification 2018 – 2022

Object detection and classification in SAR and IR imagery.

Learning to Optimize 2020 – 2022

Learning to solve combinatorial optimization problems in large distributed systems.

Distributed Learning 2020 – 2021

Reinforcement learning applied across swarms of 100s or more units.

Swarm Autonomy 2019 – 2021

Partner effort with Caltech CAST on autonomous aerial swarm systems.

Skills

Languages

C / C++Advanced

PythonAdvanced

HTML / CSSAdvanced

JavaScript / TypeScriptAdvanced

C#Intermediate

JavaIntermediate

BashIntermediate

SQLIntermediate

MIPS / RISC-VBeginner

Tools & Frameworks

AWSAdvanced

TensorFlowAdvanced

DaskAdvanced

PyTorchIntermediate

LinuxIntermediate

DockerIntermediate

SLURMIntermediate

OpenCV / scikit-imageIntermediate

scikit-learnIntermediate

CUDABeginner

Notable Projects

Sudoku Mashup Jun 2026

A Sudoku puzzle game for iOS. App Store.

Zen Brick Jan 2025

A brick-breaker game for iOS, built for fun. App Store.

Volumetric Raytracing 2017

UC Berkeley senior design project (with Noah Pitts). Recreated crepuscular rays via volumetric scattering, accelerated with NVIDIA CUDA and OptiX. Recognized as a top-10 project and showcased at semester's end. Demo.

Mastering Threes 2015 – 2017

Guided research under Prof. Stuart Russell. Monte Carlo Tree Search guided by an Inception-Net-based DQN. Demo.

3D-Printed Hexapod 2017

Designed in Fusion 360 and 3D-printed; autonomously driven by a Raspberry Pi, programmed in Python.

WiiRemote Rover 2012 – 2013

Wireless 4-wheel rover with an arm, controlled by a Wii Remote with actions previewed via a game engine. Renderer · Wii Remote.

Timbre as a Continuous Function 2014

Built a continuous function in Max/MSP interpolating between timbres — piano, violin, and flute.

Multiplayer Networking Chapter 2012

Author, networking chapter of C4 Engine: 3D Game Editing & Programming (1st ed.), ed. Dr. Mohd Fairuz Shiratuddin & Dr. Mark Fruchtaman.