Hi, I'm

Alibek Kaliyev.

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Software engineer at AWS building generative AI platforms serving 500K+ users. Pursuing MS CS at UT Austin. Originally from Kazakhstan, based in NYC.

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01. About Me

Alibek Kaliyev

I'm a software engineer passionate about building intelligent systems at the intersection of AI and cloud infrastructure. Currently at Amazon Web Services, I'm a founding engineer on the Amazon Quick Suite generative AI team, where I helped architect the entire conversational AI infrastructure from scratch.

Originally from Kazakhstan, I moved to the US for my education and have been building at the intersection of ML research and production systems since my freshman year. I speak English, Russian, and Kazakh. Beyond engineering, I'm a 2nd-degree black belt with 33 competitions under my belt — martial arts taught me the discipline and resilience I bring to every technical challenge.

Location New York City, NY
Origin Kazakhstan
Education MS CS @ UT Austin (4.0 GPA)
Languages English, Russian, Kazakh

02. Experience

Amazon Web Services

Current

Software Development Engineer — Amazon Quick Suite Team

January 2025 — Present · New York, NY

Founding engineer on a 6-person team building Amazon Quick Suite, a generative AI platform serving 500K+ monthly users. Architected end-to-end conversational AI infrastructure including networking, APIs, testing frameworks, CI/CD pipelines, and performance benchmarking systems.

Zero-to-Production in 1 Week

Drove deployment of Muse artifact generation agent by conducting A2A vs MCP trade-off analysis and delivering executive demo that secured continued investment

Multi-Agent Infrastructure

Pioneered A2A server on internal Amazon framework, establishing reusable deployment patterns for standardized agent-to-agent communication at scale

Team Velocity & Quality

Created cross-team testing framework accelerating dev velocity by 70%; led team with 584 code reviews (41% of total) averaging 1-hour turnaround

Java TypeScript AWS CDK AWS Fargate A2A Protocol Bedrock

Amazon Web Services

Software Development Engineer — Amazon Q Business Team

June 2024 — January 2025 · New York, NY

Built enterprise analytics and data infrastructure for Amazon Q Business, serving 1M+ customers across 4 regions.

Analytics Dashboard

Architected active user metrics system (DAU, WAU, MAU) with complex time-series aggregation, achieving 100% uptime over 1 year in production

Critical Pipeline Fix

Identified data pipeline failure affecting 67 enterprise customers and 46K+ requests by deep-diving Kinesis error handling; mentored intern driving permanent solution

50% Performance Boost

Improved MS Teams Connector throughput from 4 to 6 files/sec by architecting intelligent entity caching and preloading strategy

Java TypeScript AWS CDK DynamoDB Lambda Kinesis
SDE Intern — Edge ML Services

Amazon Web Services

May 2023 — August 2023

Designed automated CloudFormation stacks updater in CI/CD pipeline, making team deployments 15x faster. Shipped production code 3x faster than expected. Coordinated across 3 teams to integrate the service.

AWS CDK Step Functions Lambda CloudWatch
ML Technical Associate

GrainBound, LLC

February 2022 — May 2023

Developed and applied ML techniques for a large international chemicals manufacturer. Improved manufacturing efficiency by 40% by providing predictive insights on 50K+ row datasets.

Python TensorFlow Scikit-learn Pandas
ML Engineer — Capstone for Merck & Co.

Machine-Assisted Contextualization

January 2023 — December 2023

Led ML pipeline for pharmaceutical label classification achieving $500K annual cost savings. Improved accuracy from 47% to 92% via feature engineering (10x efficiency gain), then to 96% with semi-supervised GAN-BERT. Deployed on AWS with FastAPI.

Python PyTorch Scikit-learn FastAPI AWS

03. Ventures

Co-founder & Technical Lead

SteppeTech Consulting

January 2024 — March 2024

Founded AI consulting firm and architected computer vision-powered trademark search platform for IP-Assist Patent Office using CLIP embeddings and AWS Elasticsearch. Reduced search latency by 80% and achieved 65% cost reduction across 100K+ trademark images.

Python AWS React CLIP Elasticsearch

04. Research

Undergraduate DL Researcher · June 2020 – Dec 2023

Multifunctional Materials & Machine Learning Group

Accelerated extraction of mechanical properties of quantum materials by 3.5x using deep convolutional autoencoders. Reduced model size by 3,000x via quantization-aware training. Preprocessed 1.3M data samples. Prepared FPGA deployment achieving 40μs/fit latency.

PI: Dr. Joshua C. Agar · Lehigh University

PyTorch hls4ml AutoQKeras FPGA
Research Assistant · Aug 2022 – Mar 2023

Brain Imaging & Computation Lab

Developed Graph Attention Neural Networks for depression severity prediction, achieving R² = 0.91 between predicted and true values of Beck Depression Inventory (BDI) and Spielberger Trait Anxiety Inventory (TAI).

PI: Dr. Yu Zhang · Lehigh University

Graph Neural Networks PyTorch Neuroimaging

Publications

NeurIPS 2023 AI for Accelerated Materials Design Workshop

Rapid Fitting of Band-Excitation Piezoresponse Force Microscopy Using Physics Constrained Unsupervised Neural Networks

A.T. Kaliyev, R. Forelli, P. Sales, S. Qin, Y. Guo, S.O. Memik, M.W. Mahoney, A. Gholami, R.K. Vasudevan, S. Jesse, N. Tran, P. Harris, M. Takáč, J.C. Agar

View Paper
Advanced Materials Journal Article

Why it is Unfortunate that Linear Machine Learning Models “Work” so well in Electromechanical Switching of Ferroelectric Thin Films

S. Qin, Y. Guo, A.T. Kaliyev, J.C. Agar. Advanced Materials. 2202814, 2022.

Selected Presentations

Gulf Coast Undergraduate Research Symposium Rice University · Oct 2022
Fast Machine Learning for Science Workshop SMU · Oct 2022
MSE Undergraduate Research Symposium Lehigh University · Sep 2021
Drexel AI Research Conference Most Novel Research Award · May 2021
Center for Nanophase Materials Sciences User Meeting Oak Ridge National Lab · Aug 2020
Google Scholar Profile

05. Education & Teaching

In Progress

The University of Texas at Austin

MS in Computer Science

Machine Learning Specialization · GPA: 4.0/4.0

Part-time while working at AWS · Expected Dec 2027

Deep Learning, Advances in Deep Learning, Reinforcement Learning, Parallel Systems

Completed

Lehigh University

BS in Computer Science & Business

Magna Cum Laude · GPA: 3.78/4.0 · Minor: Cognitive Science

VP of CS & Business Association · Secretary, Central Asian Students Association

Teaching — Lehigh University

Computer Vision (CSE 398/498) Course Assistant · Spring 2024
Database Systems & Applications (CSE 241) Grader · Fall 2023
Data Structures & Algorithms (CSE 017) Course Assistant · Fall 2022 & Spring 2023
Introduction to Programming (CSE 007) Course Assistant · Spring & Fall 2021

Honors & Awards

Trustees Scholarship Top 1% of applicants · $30K/year
Most Novel Research Award Drexel AI Research Conference
Beta Gamma Sigma Honor Society Top 10% of business undergraduates
Nano-Human Interfaces Presidential Fellowship $8,000 research fellowship
STEM-SI Fellowship $5,500 research fellowship
Facebook ABCS Fellowship 2021
Dean's List Fall 2020 – Spring 2023
Data for Impact Fellowship 2020

06. Skills

Languages

Python Java TypeScript C/C++ SQL HTML/CSS

ML & Data Science

PyTorch TensorFlow NumPy SciPy Pandas Scikit-learn Matplotlib

Cloud & Infrastructure

AWS (CDK, Lambda, Fargate, DynamoDB, Kinesis, S3) Docker CI/CD React Git Google Cloud

AI & Systems

Multi-Agent Systems A2A Protocol Bedrock Reinforcement Learning Computer Vision Deep Learning