Muhammad
Ihsan

Platform Engineer with 5+ years of experience designing, automating, and operating AWS-based production infrastructure at scale. Specialized in Terraform, Kubernetes, Helm, ArgoCD, GitOps, cloud security, and reliability engineering. Currently completing my Master's in Artificial Intelligence at Johannes Kepler University Linz.

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Vienna, Austria

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Professional Profile

Cloud Engineering Meets Artificial Intelligence

Combining 5+ years of AWS platform engineering experience with graduate-level expertise in Artificial Intelligence, and modern AI systems.

Cloud & Platform Engineering

5+ years building and operating AWS-based production infrastructure

Infrastructure as Code with Terraform and CloudFormation

Kubernetes, Helm, GitOps, and ArgoCD deployment workflows

Cloud security, IAM governance, RBAC, and Secrets Management

Observability using Prometheus, Grafana, and CloudWatch

Python and Bash automation for operational excellence

Artificial Intelligence

Master of Science in Artificial Intelligence (JKU Linz)

Research in robust multimodal machine learning

Experience with LLMs, AI agents, and Generative AI

Understanding of MLOps and AI infrastructure requirements

Practical experience with OpenAI and Hugging Face ecosystems

Bridging modern AI systems with scalable cloud platforms

Career

Professional Experience

Building secure, scalable AWS platforms, Kubernetes infrastructure, and cloud automation solutions powering production workloads at scale.

Cielo Wigle Inc.

Platform Engineer

Remote — United States

Jul 2022 – Present

99.9% service availability across AWS infrastructure supporting millions of connected IoT devices.
60% faster infrastructure provisioning through Terraform and CloudFormation automation.
Migrated production workloads from AWS Lambda to Kubernetes-based platforms.
Executed DynamoDB-to-PostgreSQL migration without production downtime.
40% faster incident resolution through CloudWatch, Prometheus, and Grafana observability.
70% reduction in manual operational effort through Python automation and ETL tooling.
Implemented GitOps delivery pipelines using Kubernetes, Helm, and ArgoCD.
Strengthened platform security with IAM governance, RBAC, Secrets Manager, and network segmentation.

AWS Terraform CloudFormation Kubernetes EKS Helm ArgoCD GitOps Python PostgreSQL CloudWatch Prometheus

EDWIZ Solutions

Software Engineer

Lahore, Pakistan

Mar 2021 – Jun 2022

Developed and maintained backend services and REST APIs using Python for production web applications.
Designed and optimized database-driven systems while integrating Elasticsearch for search, analytics, and operational reporting.
Built CI/CD pipelines and automated deployment workflows, improving software delivery efficiency and release reliability.
Collaborated with cross-functional engineering teams to deliver scalable, maintainable, and high-quality software solutions.
Contributed to cloud migration, deployment automation, and observability initiatives that laid the foundation for future platform engineering responsibilities.

Python REST APIs PostgreSQL Elasticsearch CI/CD Git Linux

Work

Key Engineering Initiatives

Selected production projects and platform improvements delivered across AWS infrastructure, Kubernetes, automation, and data platforms.

AWS Lambda to Kubernetes Migration

Led the migration of production workloads from AWS Lambda to Kubernetes-based services, overcoming serverless execution limitations while improving scalability, deployment flexibility, observability, and operational control.

K8s

Platform Migration

AWS

Container Platform

Prod

Zero Downtime

Kubernetes Docker Helm AWS

DynamoDB to PostgreSQL Migration

Designed and executed migration of relational workloads from DynamoDB to Amazon RDS PostgreSQL, improving reporting, analytics capabilities, and query performance without disrupting production systems.

Production Downtime

RDS

PostgreSQL

ETL

Data Migration

PostgreSQL Amazon RDS DynamoDB

GitOps Platform & Infrastructure Automation

Built Infrastructure-as-Code and GitOps workflows using Terraform, CloudFormation, ArgoCD, GitHub Actions, and Kubernetes, reducing provisioning time by over 60% and improving deployment reliability.

60%

Faster Provisioning

IaC

Fully Reproducible

GitOps

Automated Delivery

Terraform CloudFormation GitHub Actions

Education

🎓

Master of Science (MSc), Artificial Intelligence

Johannes Kepler University Linz

Oct 2024 – Jul 2026 (Expected) · Linz, Austria

Research focused on robust multimodal learning under missing and heterogeneous inputs. Coursework includes Machine Learning, Deep Learning, Reinforcement Learning, Computer Vision, Robotics, and Multimodal AI.

Machine Learning Deep Learning Computer Vision Robotics

🎓

Bachelor of Science (BS), Information Technology

Punjab University College of Information Technology

Oct 2017 – Jul 2021 · Lahore, Pakistan

Strong foundation in software engineering, databases, computer networks, distributed systems, and application development.

Software Engineering Databases Networks Programming

Research

Research & AI Projects

Machine learning and multimodal AI research conducted during my Master's studies at Johannes Kepler University Linz.

Geometry-Preserving Prototype Learning for Robust Multimodal Fusion under Missing and Heterogeneous Inputs

Master's Thesis

Institute of Computational Perception | JKU Linz

Researching modality-invariant representations for multimodal AI systems operating under missing or degraded inputs. The work investigates geometry-preserving prototype learning techniques and evaluates robustness of multimodal foundation models across multiple benchmark datasets.

Multimodal Learning PyTorch AI Robustness Research

Revisiting ST-GCN: Differentiating Similar-Looking Industrial Activities in Real-World Scenarios

Seminar in AI & Practical Work in AI

Institute of Pervasive Computing | JKU Linz

Designed and evaluated a human activity recognition system using motion capture data and Spatial-Temporal Graph Convolutional Networks (ST-GCN). Built an end-to-end pipeline covering data collection, preprocessing, model training, evaluation, and real-time inference for industrial activity classification.

ST-GCN Graph Neural Networks Motion Capture PyTorch

Professional Presence

Community & Recognition

Technical contributions, community engagement, and recognition beyond engineering and research.

Face of JKU 2025

JKU Models 2025

Selected as one of the students representing Johannes Kepler University Linz in the official 2025 university image campaign and marketing materials.

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Stack Overflow

193K+ People Reached

Member for 6 years. Technical answers viewed by more than 193,000 developers. Earned 22 community badges through peer-reviewed contributions in software development.

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DEV Community

1000+ Followers

Technical Writing. Member for 3 years. 1,000+ followers; published architectural deep-dives on programming internals.

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IAESTE Vienna

Volunteer

Supporting international student exchange. Co-organised Teconomy 2025, the largest tech job fair at TU Wien.

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PyPI Package Author

cielo-connect-api

Published and maintained an official Python package for Cielo Connect cloud APIs. Designed asynchronous SDK functionality for device monitoring, automation, and cloud integration.

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Coding Club Vienna

Community Member

Participant of Vienna's Coding Club community. Collaborating with developers, sharing projects, exchanging ideas, and contributing to peer learning through regular coding meetups.

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