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  • Kabul, Afghanistan

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starkbaknet/README.md

Salim Baktash

Full Stack Developer

About Me aka StarkBak

Full Stack Developer with 5+ years of experience building scalable, production-grade systems.

I specialize in:

  • Distributed backend systems & microservices
  • High-performance APIs and event-driven architectures
  • Applied AI systems (RAG, embeddings, semantic search, MCP tooling)

Currently focused on bridging backend engineering + AI infrastructure to build intelligent, scalable systems.

Core Skills

Backend Engineering

Go · TypeScript · NestJS · PostgreSQL · gRPC · Kafka · Redis · Docker · Microservices

Applied AI Engineering

RAG Systems · Vector Databases (pgvector) · Embeddings · Semantic Search · MCP · LLM Integrations

Cloud & DevOps

AWS · Kubernetes · CI/CD · GitLab · GitHub Actions · Linux · Nginx

Frontend (Supporting)

React · Next.js · React Native · TypeScript

Experience

Senior Backend Engineer — Netlinks Inc (2024 – 2026)

  • Built scalable microservices using Go & NestJS for high-concurrency systems
  • Reduced event-processing latency by ~40% using Kafka pipelines
  • Improved system observability and deployment workflows
  • Integrated 10+ third-party APIs and services

Full Stack Engineer — Listoli LLC (2024)

  • Built scalable marketplace and e-commerce platforms
  • Improved API performance by 25% via caching & query optimization
  • Designed RBAC + secure authentication systems
  • Managed Docker-based deployments with PostgreSQL

Software Engineer — Top In Town Technology (2021 – 2023)

  • Built production full-stack applications with Node.js & React
  • Improved system reliability through refactoring & monitoring
  • Delivered features in cross-functional teams

Projects

jobs.af — Backend Team Lead (Link)

  • Microservices platform for job matching system
  • Built semantic job-candidate matching using embeddings + gRPC
  • Implemented vector similarity ranking for recommendations

Project Vectorizer (Source)

  • Built codebase vectorization system for AI agents
  • Enabled semantic navigation of large repositories
  • MCP-compatible architecture for contextual understanding

AI Spam Detection System (Source)

  • NLP moderation pipeline using Transformers
  • Combined zero-shot classification + risk scoring

Focus Areas

  • Backend Architecture & System Design
  • Scalable AI Infrastructure
  • Vector Search & RAG systems
  • Distributed Systems & Performance Optimization

Contact

Open to remote opportunities in:

  • Backend Engineering
  • Platform Engineering
  • Applied AI Infrastructure

Email: baktash775@gmail.com
Portfolio: https://baktash.starkbak.net

Pinned Loading

  1. project-vectorizer project-vectorizer Public

    A CLI tool that vectorizes codebases, stores them in a database, tracks changes, and serves them via MCP (Model Context Protocol) for AI agents like Claude, Codex, and others.

    Python 2 1

  2. mozho_chat mozho_chat Public

    A scalable, secure chat application backend built with Go, featuring real-time messaging, file attachments, end-to-end encryption, and modern architecture patterns.

    Go

  3. web-spider web-spider Public

    A fast, scalable, and concurrent web crawler built in Rust, using Redis as a distributed queue and Docker for orchestration.

    Rust

  4. job-recommendation-system-ts job-recommendation-system-ts Public

    A high-performance job recommendation system built with TypeScript, Express, TypeORM, and PostgreSQL. The system uses vector embeddings and cosine similarity to provide accurate, personalized job r…

    TypeScript

  5. spring-boot-batch-processing spring-boot-batch-processing Public

    A minimized Spring Boot application for processing course invitations using batch processing.

    Java

  6. ai-image-dectector ai-image-dectector Public

    A sophisticated command-line tool to detect whether an image is AI-generated or real using 10 different detection methods and intelligent multi-signal analysis.

    Python 2