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About

Engineer who ships, learns in public, and documents the journey.

I'm Balraj Yadav — known on GitHub as Balu Yadav. I build full stack web applications and care about what happens after the deploy — uptime, observability, and cost. I'm currently growing into a Cloud and DevOps role and using AI tools to compound the work.

Background

I started with frontend, fell for the ergonomics of TypeScript and the App Router, and then kept following the request all the way down — Node, Postgres, Docker, Linux, Nginx, AWS. Once you've chased a 502 from the browser to a misconfigured security group at 3am, infrastructure stops feeling abstract.

These days my work splits between three things: shipping product features in Next.js, automating the boring parts of deployment and operations, and integrating AI tools into the engineering loop in ways that pay for themselves.

How I work

  • Default to small, reversible changes with a tight feedback loop.
  • Type the boundary, log the failure mode, version the infra.
  • Write the README on day one, not the day before handoff.
  • If a task happens twice, it gets a script. Three times, a pipeline.

What I'm looking for

A production-focused full stack / cloud engineering role where I can own delivery end-to-end — from API design through CI/CD and observability. Bonus points for teams that take docs and DX seriously.

Experience

Designations & journey

Roles, learning phases, and what I shipped along the way.

  1. Full Stack Developer

    Hitech People Inc.

    Jan 2024 — Present

    Building web applications and internal tooling while growing into cloud and DevOps. Pairing day-to-day product work with deliberate practice in CI/CD, containers, and AI-assisted engineering.

    • Contributing to Next.js applications used internally and by clients
    • Practicing Docker, GitHub Actions, and Linux administration on real workloads
    • Using AI tools (Claude, Cursor) to accelerate review, refactors, and documentation
    Next.js
    TypeScript
    Node.js
    Docker
    GitHub Actions

  2. Self-directed cloud & DevOps track

    Personal study

    Jun 2023 — Present

    Structured learning path through Linux, networking, Docker, CI/CD, and cloud — alongside the day job. Output is captured in the Cloud & DevOps Lab section and the writing notes on this site.

    • Linux administration: SSH hardening, systemd services, shell scripting
    • Containers and CI/CD: multi-stage Docker builds, GitHub Actions pipelines
    • Cloud foundations: AWS EC2/S3/IAM hands-on, Terraform reading and writing
    • Observability lab: Prometheus, Grafana, and Loki on a single VPS
    Linux
    Bash
    Docker
    GitHub Actions
    AWS
    Terraform
Skills

What I work with

Grouped by area, with proof of work where it exists. No meaningless progress bars — just where the skill has been used.

Frontend

Component-driven UIs with strong typing and accessibility.

Backend

API design, server-side logic, and persistence.

  • Node.js
  • Express
  • REST APIs
  • PostgreSQL
Cloud & DevOps

Repeatable provisioning, packaging, and delivery.

  • AWS (EC2 / S3 / IAM)
  • Docker & Compose
  • Linux administration
  • Nginx + TLS
  • GitHub Actions
  • Terraform (IaC)
Observability

Metrics, logs, and alerts that surface real failure modes.

  • PrometheusInfra Monitor lab
  • Grafana
  • Loki + Promtail
  • Alertmanager
  • Runbooks
  • SLOs & dashboards
AI Engineering

Practical LLM workflows that pay back in engineering time.

  • LLM workflows
  • RAG patterns
  • Prompt engineering
  • AI-assisted debugging
  • DevOps copilots
  • Claude API & Code
Engineering Practices

How the work gets shipped, kept honest, and learned from.

  • CI/CD pipelines
  • System design basics
  • Documentation
  • Runbooks & incident notes
  • Deployment thinking
  • Code review with AI

Let's build something solid.

I'm open to full stack, cloud, and DevOps roles, plus selective freelance work. The fastest reply is by email.

Get in touchEmail me