Backend / Platform Contracts
Can he build or stabilize the core system?
/backend-platform
open to work · remote
Senior backend engineer & technical lead. Distributed systems, payments, AI-native.
Reliable distributed platforms, AI automations, developer tools, quality systems, and AI-ready knowledge bases for teams that need leverage.
Talk to my assistant about your project Explore proof library
double-processed payment events 0
events/day 1M+
report generation (from ~30s) <2s
incident MTTR 20→5min
01 · directions
Three ways I create leverage
01
AI automations
Agent workflows, LLM integrations, and pipelines that turn repetitive work into supervised automation.
02
Platform systems
Backend services, integrations, and data-intensive systems built for reliability and long-term maintainability.
03
AI development culture
Plugins, prompt systems, review rituals, and team practices that make AI tooling work like serious engineering.
02 · services
Service snapshot
AI Automation Systems
Can he turn our repetitive work into an AI-assisted workflow?
/ai-automation
AI Development Culture
Can he help our team use AI like serious engineers?
/ai-dev-culture
Quality + Knowledge Systems
Can he make our engineering work more controlled and reusable?
/quality-knowledge
03 · proof
Proof preview
Architecture decision
ClickHouse reporting and analytics service for a B2B payments platform
Problem A B2B payments platform needed aggregation, analytics, and metrics over growing operational data; running analytical queries on the transactional PostgreSQL database was slow and put the payment path at risk.
Result A reporting system that serves analytics and metrics without touching the transactional path — cutting report generation from ~30s on PostgreSQL to under 2s on ClickHouse, and staying fast as volume grew past 1M+ events/day.
System
Payments platform microservices — billing, notifications, crypto integrations
Problem A B2B payments platform needed new product capabilities — billing, email notifications, cryptocurrency integrations — without destabilizing the existing system or risking the money-critical payment path.
Result A fault-tolerant microservice architecture where new services ship without risking the core payment path — with zero double-processing of payment events under retries. Led the team of 4 engineers delivering it.
System
Grounded RAG assistant running in production
Problem Visitors want a fast, honest answer on whether there's a fit — but generic chatbots hallucinate, leak their system prompt, and can be hijacked by instructions hidden inside user messages (prompt injection).
Result A live, self-hosted production LLM system — not a demo — serving real visitor traffic on this site, grounded enough to cite its sources and safe enough to refuse out-of-scope or injected requests.
04 · fit
Fit matrix
fit-check.diff --unified
- @@ strong fit @@
- Backend/platform contracts: APIs, integrations, internal platforms, reliability work.
- AI automation projects: agent workflows, LLM integrations, document and data pipelines.
- AI development culture: plugins, workflows, review rituals, team enablement.
- Quality and knowledge systems: QA gates, evaluation loops, AI-readable documentation.
- Technical leadership: tech lead, CTO, or fractional CTO for small teams.
- @@ not a fit @@
- Pure frontend/design projects with no backend or systems component.
- ML research or training models from scratch.
- Staff augmentation without ownership of outcomes.
- Projects that need promises of guaranteed delivery dates before scoping.