I believe in a secure-by-default, scalable, and highly automated approach, ensuring that cloud infrastructure handles any scale while remaining secure and cost-efficient.
Technical Skills
Core cloud provider used for deploying scalable, secure, and reliable infrastructure.
Used for specialized Generative AI workloads and multi-cloud solutions.
Deploying, managing, and scaling virtual machines with optimized configurations.
Custom network topologies, public/private subnets, and routing security.
Relational database service configured for high availability and failover.
Secure, durable, and highly-scalable object storage with policy enforcement.
Fine-grained access controls, role assumptions, and least-privilege security.
Serverless compute execution for event-driven automation and APIs.
Designing private/public layouts, NAT gateways, and Route Tables for security.
Application Load Balancers for high availability and traffic routing.
Elastic capacity adjustment based on traffic spikes and demand metrics.
Containerizing multi-tier applications to ensure environment consistency.
Orchestrating container workloads in scalable AWS cluster environments.
Infrastructure as Code (IaC) to provision cloud resources repeatably.
Reverse proxy, load balancer, and secure web server configuration.
Automating build, test, and container deployment pipelines.
Distributed version control and collaboration management.
Main scripting language for AI models, backends, and automation.
Micro web framework for creating RESTful APIs and microservices.
Server management, shell scripting (Bash), and process optimization.
Relational database administration and query design.
Fully managed NoSQL database for fast, flexible cloud storage.
Orchestrating LLMs, chains, prompt templates, and retrieval-augmented generation.
Facebook AI Similarity Search for high-performance vector retrieval.
Prompt engineering, structural output generation, and token management.
Node-based automated workflows connecting AI agents and APIs.
AWS Architecture Showcase
Interactive schematic of the secure, multi-tier AWS Infrastructure designed to host production systems. Click on any component node to inspect its operational role, security boundaries, and communication protocol.
Cloud & DevOps Journey
Tracing the evolutionary path of specialized knowledge from core OS administration to automated cloud infrastructure and Generative AI systems.
Linux Administration
Foundational Systems LayerBegan journey mastering operating systems fundamentals. Learned shell scripting (Bash), access permissions, service configs (systemd), processes management, and secure SSH tunneling.
Networking Essentials
Bridges and BoundariesGained absolute clarity on networking protocols, subnet calculations (CIDR), routing, domain management (DNS), firewalls, reverse proxy logic, and securing Layer 7 protocols.
AWS Infrastructure
Scale to the CloudsTransitioned local workflows into the cloud. Designed highly resilient, isolated multi-tier networks using AWS VPC, routing tables, EC2 instances, RDS databases, S3 object storage, and IAM least-privilege security.
Docker Containers
Consistency at Any ScaleAdopted container-centric architectures. Wrote optimized multi-stage Dockerfiles to isolate Flask/Python backend APIs, minimizing load images and managing container environments.
Terraform (IaC)
Infrastructure as CodeStandardized infrastructure deployment. Wrote scalable, modular declarative scripts using Terraform to build, modify, and track cloud state repositories repeatably.
CI/CD Automation
Continuous Integration / DeliveryAutomated release and deploy processes. Constructed build pipelines using GitHub Actions to trigger automated image packaging, testing, and continuous deployments (CD) on virtual servers.
Generative AI Engineering
Intelligent Cloud AppsIntegrated intelligent logic with systems. Built Retrieval-Augmented Generation (RAG) structures, FAISS vector index searches, LangChain conversation interfaces, and automated workflows using n8n.
Cloud & DevOps Engineer
Modern Systems ArchitectureOperating at the intersection of secure infrastructure provisioning, automated CI/CD flow, container orchestration, and Generative AI backend application layers.
Open Source
Actively contributing to AI development tools, data science systems, and documentation ecosystems.
OpenAI Codex Documentation Contribution
Contributed documentation fixes and usage patterns to OpenAI Codex, detailing prompt structure and code generation interfaces. Merged in 2024.
Pandas Data Verification Optimization
Contributed structural improvements and performance optimizations to Pandas core processing, enhancing data validation routines and error checks.
Certifications
Validated professional capabilities in Cloud Platforms, Generative AI models development, and systems development.
Google Cloud GenAI Academy
Advanced validation in generative AI architectures, large language model fine-tuning, retrieval pipelines, and building agents.
AWS Cloud Quest: Cloud Practitioner
Hands-on validation of AWS core services, cloud security, networking, pricing, and infrastructure automation.
IBM Python for Data Science & AI
Deep dive into Python programming, object-oriented principles, data structures, and integration with AI libraries.
Resume
My educational background, professional experience, and technical milestones.
Abkari Mohammed Sayeem
Cloud & DevOps Engineer
BCA graduate specializing in Artificial Intelligence with hands-on experience designing and deploying multi-tier applications and infrastructure on AWS.
Download Full CV (PDF)Work Experience
AI / ML Intern
Sep 2024 – Oct 2024Elewayte
- Built and evaluated supervised ML models (Logistic Regression, SVM, Random Forest) in Python, achieving up to **88% validation accuracy** across 5+ structured datasets.
- Translated model evaluation results into clear, actionable summaries for stakeholders to support data-driven decisions.
- Performed end-to-end ML workflows including data preprocessing, EDA, feature engineering, and model evaluation using Pandas, NumPy, and scikit-learn.
- Maintained project code and collaboration using Git and GitHub, building team-oriented version control habits.
Education
Bachelor of Computer Applications
Class of 2026Specialization: Artificial Intelligence
Dr. B B Hegde First Grade College, Mangaluru
Core Coursework focusing on cloud computing, data systems, and machine learning architectures.
CGPA achieved: 7.28
Languages
Engineering Notes
Articles and research notes on system configurations, virtualization, secure cloud topology designs, and DevOps processes.
Why Private Subnets Matter
Understand the security implications of placing databases and backend services in public vs private subnets, and how NAT Gateways control outgoing traffic.
Gunicorn vs Flask
Learn why you should never run your Flask application in production using the built-in development server, and how Gunicorn manages concurrent requests.
How ALB Works
An in-depth look at Application Load Balancer routing algorithms, health checks, SSL offloading, and integration with Auto Scaling Groups.
Dockerizing Flask
Step-by-step guide to writing optimized multi-stage Dockerfiles for Python Flask backends, reducing image size, and implementing security best practices.
Understanding IAM Roles
Why you should never store AWS access keys on EC2 instances, and how IAM Roles securely provide temporary credentials via the metadata service.
VPC Networking Explained
Demystifying subnets, CIDR blocks, route tables, and firewalls (Security Groups vs NACLs) for a production-ready AWS VPC setup.