Full-Stack Software Architect — I build production systems from database to UI, augmented by AI-driven workflows that accelerate delivery without cutting corners on quality, observability, or maintainability.
- Make architectural decisions — choose frameworks, databases, hosting strategies, and state management approaches based on team size, traffic patterns, and business constraints. Default to simple until complexity is proven necessary.
- Design for production — observability (structured logging, metrics, tracing), graceful error handling, rate limiting, caching strategies, DB indexing, migration plans, and zero-downtime deploys.
- Write and review code that prioritizes readability, testability, and consistent patterns. Set up linting, formatting, CI/CD, and code review standards that let the team move fast without chaos.
- Own incidents end-to-end — from on-call response and root-cause analysis to follow-up PRs that prevent recurrence. Treat every outage as a system improvement opportunity.
- Leverage AI-augmented development — use LLM-assisted coding, agentic scaffolding, and automated review loops as force multipliers, while maintaining full ownership of architecture, correctness, and production readiness.
- Communicate across roles — translate technical tradeoffs into product decisions for PMs and stakeholders. Write RFCs and design docs that capture context, alternatives, and rationale.
- Mentor and raise the bar — unblock teammates, model effective code review, and push for better abstractions without over-engineering.
| Area | What that means |
|---|---|
| System design | Modular monoliths, service boundaries, API contracts (REST), caching layers, auth flows (session, JWT, OAuth), rate limiting, background job queues |
| Frontend | Component architecture, state machines over ad-hoc state, error boundaries, bundle analysis, SSR/SSG/ISR tradeoffs, a11y baseline (keyboard nav, ARIA, contrast) |
| Backend | Layered services (controller → use-case → repository), request validation, middleware composition, migration-driven schema changes, idempotent mutations |
| Data | Query planning (EXPLAIN ANALYZE), index strategy, migration rollback plans, connection pooling, read replicas, event-sourced audit logs where required |
| Production | Structured logging (structured + correlated), health checks, circuit breakers, feature flags, staged rollouts, runbooks for common failure modes |
| DX & tooling | CI/CD pipelines (lint → typecheck → test → build → deploy), monorepo conventions, dependency management, environment parity, pre-commit hooks |
| Language | TypeScript (typed states, branded types, generics), SQL (window functions, CTEs, recursive queries) |
- Agentic workflows and LLM-integrated application architectures
- Web3 primitives and decentralized data patterns
- Russian (learning the language)
I believe the best software is boring software — predictable, testable, and replaceable. I'm increasingly interested in systems where the frontend is a thin, fast client over a well-typed API, and where state is explicit, not implicit.
- LinkedIn — professional
- tarpagajd@gmail.com — direct
- Telegram — casual