Production backend
APIs, service boundaries, data workflows, maintainable internals, and practical reliability work.
Backend engineer focused on GCP and AI systems
Building reliable backend platforms for cloud and AI workflows.
I am Blazej Pajor, a Software Engineer working across Go, PHP, Google Cloud, Kubernetes, and LLM-based automation. I care about clean architecture, ownership, and systems that stay understandable after they reach production.
Current
WP Engine
Focus
GCP / AI
Mode
Production
Engineering profile
I work where backend reliability meets cloud operations.
At WP Engine, I design, build, and maintain scalable systems with Go, PHP, Google Cloud Platform, and Kubernetes. My work sits close to reliability, performance optimization, and operating cloud infrastructure that has to keep behaving under real production pressure.
Working principles
Clean boundaries over clever abstractions
Operational clarity before feature volume
Security and cost treated as design inputs
Automation that remains explainable
Cloud operations
GCP, Kubernetes, observability, performance tuning, and infrastructure shaped by cost and security constraints.
Agentic AI
LLM-based workflows, MCP interfaces, and automation that gives agents useful context without exposing unsafe tools.
Selected projects
Practical systems, APIs, and internal tooling.
Short case studies focused on the engineering context, technical decisions, and what each implementation demonstrates.
Business operations
Pay Management System
A system for monitoring employee payouts and keeping payroll-related workflows visible to internal users.
Problem
Payroll visibility usually breaks down when calculations, approvals, and operational status live in separate places.
Built
Designed an application surface for tracking payout state, business rules, and operational review paths.
Signals
Domain modelingWorkflow stateAdmin-facing UX
BackendBusiness logicInternal tooling
View case study
Public data API
PolElections2023 REST API
A REST API exposing Polish parliamentary election results from 2023 through structured endpoints.
Problem
Election data is useful only when it can be queried predictably by district, committee, candidate, and result scope.
Built
Implemented an authenticated API layer for exploring election results and related entities through clear REST contracts.
Signals
API designJWT authStructured public data
Nest.jsTypeScriptMongooseJWT
View case study
Writing
Technical writing as an engineering notebook.
I want the blog to document how systems are designed, shipped, operated, and improved. Posts will be written for engineers first, while still being structured enough for search engines and AI agents to understand the context precisely.
Go backend architecture
API design, service boundaries, SQL workflows, and production-grade implementation details.
GCP and Kubernetes operations
Reliability, observability, performance, and cost-aware cloud infrastructure.
LLM systems and MCP
Agent interfaces, safe tools, and AI workflows that fit real engineering constraints.
content pipeline
01 admin panel publishing
02 PostgreSQL-backed posts
03 RSS, sitemap and JSON-LD
04 MCP-readable site context
Built to be readable by humans, crawlers, and authorized agents without hiding content or relying on SEO tricks.