How we can
work together.

Backend & systems engineering

I design and build APIs, data models, and background work that stay reliable when traffic and scope grow.

• Greenfield services or careful rewrites of code that has outgrown its first shape.
• Postgres, MySQL, MongoDB, Redis, and queue-based jobs wired with clear ownership and error handling.
• Integrations with billing, email, auth, and third-party APIs your product already depends on.
• Logging, metrics, and runbooks so your team can operate the system without guessing.

AI tooling & integration

I treat LLM features as product engineering: retrieval, evals, cost control, and behavior you can explain to stakeholders.

• RAG pipelines and chat experiences grounded in your own docs, APIs, or content.
• Prompt and model routing through gateways (including OpenRouter) with fallbacks and limits.
• Eval harnesses and test sets so quality does not depend on one manual chat session.
• Instrumentation for latency, token use, and failure modes before you scale usage.

Full-stack product delivery

I ship coherent slices from database to UI: one person who can own the vertical and communicate tradeoffs clearly.

• React or Next.js front ends with typed APIs (Node, Django, or FastAPI depending on fit).
• Auth, roles, and multi-tenant patterns where the business rules need to live in one place.
• CI, Docker, and deployment paths that match how your team already ships.
• Pragmatic test coverage on the paths that break most often in production.

Automation & data pipelines

I replace brittle scripts with workflows you can see, replay, and fix when something fails at night.

• n8n, cron, and queue-driven pipelines for content, ops, and internal tooling (see the n8n Automation project).
• Idempotent steps, retries, and alerts when a node fails or data drifts.
• Sheets, webhooks, OpenAI, CMS, and email tools connected with documented handoffs.
• Central error handling so one broken job does not silently poison downstream systems.

Web scraping & platform work

I build and extend scraping infrastructure: proxies, parsers, monitoring, and the unglamorous middleware around them.

• Proxy rotation, geo targeting, and health checks (aligned with work like ScrapeOps and XProxy Tester).
• Structured parsers and Scrapy job monitoring with alerts your team can act on.
• Go or Node services for high-throughput paths; Django or Express where product APIs fit better.
• Docs and operational playbooks so scraping is a managed system, not a folder of scripts.

Technical advisory

Short, direct engagements when you need an experienced second opinion before committing to a build or hire.

• Architecture reviews and written recommendations you can share with investors or your team.
• Due diligence on codebases, infra choices, or vendor integrations.
• Scoped prototype spikes to de-risk one decision, not open-ended research.
• A single readout call to walk through findings and sensible next steps.