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Hi, I'm

NAYEEM
FARDIN

AI-Native Systems Engineer

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AWS KUBERNETES FASTAPI REACT KAFKA RABBITMQ TERRAFORM POSTGRESQL GO AWS KUBERNETES FASTAPI REACT KAFKA RABBITMQ TERRAFORM POSTGRESQL GO

ABOUT.

I'm a Computer Science undergrad at Islamic University of Technology who builds AI-native systems — computer vision, RAG, and LLM pipelines — on production-grade backend foundations designed to scale and break gracefully. My focus is shipping AI features with real engineering rigor: async queues, observability, reliability engineering, and cost-conscious, cloud-native architecture.

Education

B.Sc. in Computer Science & Engineering

Islamic University of Technology (IUT)

Expected Sep 2026

IUT Logo

Tech Stack

Languages
Python Go Dart Kotlin JavaScript C++ Java
Web & API
React Node Express FastAPI
Mobile
Flutter Android
AI & ML
LangChain PyTorch RAG OpenAI
Cloud & Ops
AWS Docker Kubernetes Terraform Linux Git
Sys & Tools
Kafka RabbitMQ Celery Grafana ArgoCD Helm
Databases
PostgreSQL Redis InfluxDB Pinecone MongoDB

PROJECTS.

RetailOS Lite

RetailOS Lite supervisor overview dashboard preview
Next.js 15 TypeScript FastAPI BullMQ YOLO Prisma Modal GPU Pinecone Prometheus Grafana
  • AI-native retail execution platform featuring async YOLO shelf analysis, multi-signal fraud detection, and governed outlet master data.
  • Orchestrates an async BullMQ pipeline executing YOLO + LLM reasoning, complete with Prometheus queue metric collection and DLQ replay CLI.
  • Features a 5-signal calibrated fraud engine (SHA-256, dHash, GPS mismatch, EXIF analysis) that runs early to save expensive GPU resources.
  • Implements weighted outlet similarity matching (pg_trgm + geo prefilter) with three-tier resolution and non-destructive duplicate merging.
  • Designed a two-tier RAG operational assistant combining exact DB queries (via Prisma) with Pinecone semantic search over visit reports.
Python YOLOv11 AWS EKS FastAPI Docker ONNX Prometheus ArgoCD Helm
  • Fine-tuned and deployed YOLOv11L on AWS EKS as a microserviced inference service for dense, multi-class retail product detection.
  • Compiled the model into an in-process ONNX Runtime engine with INT8 quantization + right-sized CPU bin-packing (200m/pod) for sub-500ms detection entirely on CPU — no GPU required.
  • CPU inference speedup and 70–90% cost savings via INT8, AMX, and Spot node diversification across m7i-flex, c7i-flex, and t3.small.
  • GitOps progressive delivery: ArgoCD Image Updater polls ECR, Argo Rollouts runs weighted canaries through NGINX Ingress with automated smoke tests before promotion.
  • Spot resilience enforced with Pod Disruption Budgets and native 2-minute interruption handling for zero-downtime operation on volatile hardware.
  • DevSecOps gates in GitHub Actions (OIDC/STS)ruff, pip-audit, and Trivy CVE scans guard the ECR boundary; Loki/Prometheus/Grafana for observability.
Go Python Celery RabbitMQ Terraform AWS K3s Redis
  • Migrated the HTTP edge from FastAPI to Go, preserving full contract parity with the existing Celery worker runtime and Alembic-managed schema.
  • Architected a dual-node K3s cluster on AWS (On-Demand control + Spot data plane) with full Terraform IaC and automated SSM reconciliation for async image processing queued through RabbitMQ.
  • Optimized cost with EC2 Spot and graceful eviction via AWS Node Termination Handler.
  • Resilience under load with Redis idempotency keys, pybreaker circuit breakers, and k6 stress tests.
  • Zero-Trust GitHub Actions (OIDC) CI/CD; telemetry and traces to Grafana LGTM via Alloy.
  • Decoupled ML inference from fast conversions via dedicated queues to prevent worker starvation.
Flutter Kotlin CameraX ML Kit AlarmManager GeofencingClient MapLibre
  • Flutter/Native split: Flutter UI shell backed by a Kotlin alarm engine that owns scheduling, ringing, recovery, and dismissal authority.
  • Location alarms via GeofencingClient with hybrid geofence + passive approach-assist and 10-state health model per alarm.
  • Mission-based dismissal with native inactivity enforcement — math, steps (TYPE_STEP_DETECTOR), and QR (CameraX + ML Kit) missions.
  • Direct-boot persistence and reboot recovery before first unlock via device-protected storage and LOCKED_BOOT_COMPLETED.
  • 28-finding security/performance/reliability audit driving a dedicated hardening sprint. Macrobenchmark + Perfetto performance tooling.

More Projects.

StatusMonitor

FastAPI Kafka InfluxDB React 19

Distributed monitoring platform — FastAPI microservices, a Kafka ingestion pipeline, tiered InfluxDB retention, and real-time Telegram alerts.

Crawler RAG DocHelper

LangChain Pinecone Gemini 2.5 Cohere

Hybrid-search RAG over docs — semantic + BM25 retrieval in Pinecone, Cohere rerank, and Gemini 2.5 generation with query-time alpha tuning.

interviewPrepper

LangGraph FastAPI Multi-LLM Firecrawl

AI 30-day learning-plan generator — LangGraph agent orchestration, cross-LLM routing (OpenAI/Gemini/OpenRouter), and Firecrawl + Tavily retrieval.

RoutineMaker

FastAPI Docker Nginx PostgreSQL

Microservices routine manager — split Auth/Core FastAPI services behind an Nginx gateway, Argon2 + JWT security, and automated PDF export.

EXPERIENCE.

Intelligent Machines Logo

AI Native Engineering Intern

Intelligent Machines

June 2026 — Present
  • Building production-grade AI-native systems at a company shipping 59 production systems across 16 enterprise clients in 6 countries — including Unilever, bKash, and Banglalink.
  • Working across the AI/ML engineering stack spanning computer vision, document intelligence, and enterprise integration pipelines for trade marketing and distribution platforms.
Backdoor Private Limited Logo

CyberSecurity Internship

Backdoor Private Limited

October 2025
  • Digital forensics analysis to recover sensitive deleted artifacts using FTK Imager and Autopsy.
  • Security assessments on Android applications via MobSF and web platforms using Burp Suite and SQLMap.

LET'S BUILD
SOMETHING.

Got a project idea, internship opportunity, or just want to chat? Hit me up.