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msaleh1888/README.md

👋 Hi, I’m Mahmoud — Full-Stack Software Engineer | AI Systems | Distributed Platforms

I build production-grade software platforms, distributed backend systems, developer tooling, and AI-enabled applications across backend services, frontend products, cloud integrations, and practical AI workflows.

My recent work focuses on FastAPI backends, asynchronous workflows, Celery workers, MongoDB, Redis, React, Next.js, real-time systems, cloud integrations, and production-oriented AI products.

I bring 12+ years of engineering experience across automotive and software industries, including long-term collaboration with globally distributed engineering teams and stakeholders across Europe, North America, and the Middle East.


Current Work

Software Engineer @ Tekunda

Contributing to a production Salesforce DevOps platform and AI-enabled business applications across:

  • Event-driven notification systems
  • Backend services and async workflows
  • Celery worker systems and distributed task processing
  • Real-time updates using SSE
  • Frontend operational tooling and UX improvements
  • GitHub and GitLab source-control integrations
  • Azure Blob Storage lifecycle workflows
  • Salesforce DevOps automation workflows
  • AI product architecture, testing, integrations, and reliability improvements

Core technologies:
FastAPI, MongoDB, Redis, Celery, Next.js, React, Zustand, Tailwind CSS, Ant Design, Azure, GitHub APIs, GitLab APIs, SendGrid, OpenTelemetry, SSE/WebSockets.


Engineering Focus

  • Production-grade backend systems
  • Distributed workflows and async processing
  • Internal developer platforms and operational tooling
  • Full-stack product engineering
  • Event-driven architecture and real-time applications
  • Reliability-focused backend design
  • AI-enabled products and LLM integrations
  • Cloud integrations and source-control automation

📂 Featured Projects

🔹 Job Market Intelligence Platform

Backend-first AI platform for ingesting, enriching, and analyzing job-market data using async pipelines, LLM workflows, and a React frontend.

Highlights

  • FastAPI backend with async ingestion pipelines
  • PostgreSQL persistence and historical snapshots
  • RAG-style enrichment and recommendation workflows
  • React / Next.js frontend consuming backend APIs
  • Reliability-focused architecture with idempotent processing patterns
  • Production-style system design and modular service boundaries

Stack

FastAPI, PostgreSQL, Celery, Redis, React, Next.js, Docker, LLM APIs

🔗 GitHub:
https://github.com/msaleh1888/job-market-intelligence-platform


🔹 Multimodal Visual Inspection & Explanation API

Production-style multimodal AI service for image and document analysis using Vision-Language Models (VLMs).

Highlights

  • Image + prompt → structured reasoning pipeline
  • Grounded explanations and confidence-aware outputs
  • Clear separation between perception, reasoning, and interpretation
  • Failure-aware response handling
  • API-first backend architecture

Stack

FastAPI, PyTorch, VLMs, Python, Docker

🔗 GitHub:
https://github.com/msaleh1888/multimodal-visual-inspection-api


🔹 Azure Serverless Invoice Extraction API

Cloud-native invoice extraction service using Azure Functions and Azure Document Intelligence.

Highlights

  • Invoice → structured JSON workflow
  • Serverless deployment architecture
  • CI/CD integration and monitoring
  • Production-oriented cloud workflow design

Stack

Azure Functions, Azure Document Intelligence, Python, GitHub Actions

🔗 GitHub:
https://github.com/msaleh1888/azure-serverless-invoice-extraction


🔹 RAG Microservice

FastAPI microservice for embeddings, vector search, and grounded question-answering.

Highlights

  • Document ingestion pipeline
  • Embedding + vector-search workflow
  • Retrieval-augmented answering
  • Lightweight production-oriented API design

Stack

FastAPI, ChromaDB, SentenceTransformers, Groq

🔗 GitHub:
https://github.com/msaleh1888/rag-llm-fastapi-microservice


🛠 Tech Stack

Languages

Python, TypeScript, JavaScript, SQL

Backend & APIs

FastAPI, REST APIs, Async Programming, Celery, Server-Sent Events (SSE), WebSockets

Frontend

React, Next.js, Zustand, Tailwind CSS, Ant Design

Databases & Storage

MongoDB, PostgreSQL, Redis

AI & LLM Systems

OpenAI APIs, RAG, Prompt Engineering, LLM Integration, Embeddings, Vector Search, Multimodal AI (VLMs), Langflow, MCP

Cloud & DevOps

Docker, Kubernetes (AKS), GitHub Actions, CI/CD Pipelines, Azure, OpenTelemetry

Distributed Systems

Async Workers, Scheduled Workflows, Idempotency, Retry-Safe Processing, Background Processing

Integrations

GitHub APIs, GitLab APIs, OAuth 2.0, Webhooks, RBAC

ML & Data

PyTorch, scikit-learn, Pandas


🌍 What I’m Interested In

  • Full-Stack Software Engineering
  • AI Systems Engineering
  • Backend Platform Engineering
  • Internal Developer Platforms
  • Distributed Systems & Operational Tooling
  • Production AI Products
  • Reliability-focused Backend Engineering
  • AI-enabled Developer Workflows

📫 Contact

If you're building production software platforms, internal developer tools, distributed backend systems, or AI-enabled workflows, I'd love to connect.

Pinned Loading

  1. intel-natural-scenes-resnet18 intel-natural-scenes-resnet18 Public

    A clean, well-structured PyTorch project where I trained a ResNet18 model on the Intel Natural Scenes dataset. The repo includes modular code, a simple training pipeline, full documentation, and a …

    Jupyter Notebook

  2. intel-natural-scenes-api intel-natural-scenes-api Public

    FastAPI + Docker inference service for my fine-tuned ResNet18 Intel Natural Scenes classifier. Upload an image and get real-time scene predictions with confidence scores.

    Python

  3. rag-llm-fastapi-microservice rag-llm-fastapi-microservice Public

    Production-ready Retrieval-Augmented Generation (RAG) microservice using FastAPI, ChromaDB, SentenceTransformers, Grok (xAI), and Docker. Supports TXT/PDF ingestion, vector search, and LLM-based qu…

    Python

  4. azure-ml-customer-segmentation azure-ml-customer-segmentation Public

    Production-grade customer segmentation pipeline built on Azure (Blob Storage, Data Factory, Azure ML, Batch Endpoint). Includes end-to-end data engineering, feature engineering, K-Means model train…

    Python

  5. azure-serverless-invoice-extraction azure-serverless-invoice-extraction Public

    Serverless invoice extraction API using Azure Document Intelligence and Azure Functions. Upload a PDF invoice and receive normalized JSON output including line items, totals, dates, and vendor deta…

    Python

  6. portfolio-site portfolio-site Public

    AI Engineer / Cloud-AI Developer portfolio featuring ML, Azure, FastAPI, and RAG projects.

    HTML