Public role fit

Remote Python/backend automation, internal tools, API/CRM integration, QA Automation Python, AI workflow automation, and reliability handoff work.

I build working business systems: FastAPI/PostgreSQL backends, Telegram intake to admin workflows, RAG/transcript workflows, call-audio transcription, analysis JSON, approval flows, integration adapters, tests, smoke checks, Docker/Compose boundaries, docs, runbooks, and recovery notes.

Search-match stack: Python, FastAPI, PostgreSQL, pytest, REST APIs, OpenAPI, Docker, Docker Compose, GitHub Actions, RAG, n8n, Telegram, CRM/ERP/API integrations, workflow integration, Backend Development, QA Automation Python, Workflow Automation, audit logs, runbooks, and PostgreSQL/pgvector-backed workflows.

Fast fit checklist: remote-capable work, concrete technical outcome, real systems, and one working slice with tests, logs, docs, demo path, and handoff. Not my target right now: onsite-only roles, pure prompt/content tasks, or undefined outcomes.

Shortlist signal: messy business workflows become backend-owned systems with records, state, integrations, logs, tests, docs, and handoff. Risk I reduce: hidden automation state, brittle no-code glue, unclear adapter boundaries, missing logs, and unverified AI output.

Distributed async remote signal: written review paths, English-first docs, async technical review, privacy/integration boundaries, CI, runbooks, and timezone-friendly handoff.

AI-assisted engineering workflow: AI tooling accelerates discovery, implementation, debugging, docs, and review, while architecture, state boundaries, privacy checks, tests, logs, deployment, runbooks, and shipped quality stay engineering-owned.

Message on LinkedIn Start conversation Decision-ready contact Autoschool Intake/Admin work sample LinkedIn Services DriveDesk AI Operator route Skill evidence PDF resume

AI Automation

Document/transcript/lead intake, importable n8n workflow artifact, RAG, OpenAI/Claude/Gemini provider boundary, call-audio transcription, transcript/document workflows, scoring, routing, approvals, human review, Telegram, and CRM actions.

DriveDesk AI Operator

Role Targets

Primary target: Junior Python Backend / API Automation. Secondary lanes: QA/API Python, CRM/API Integration, Internal Tools, Support Engineer with Python, and workflow automation roles where the work is backend/API-heavy. AI workflow and RAG stay visible as evidence-backed differentiators, not the first title I need to be screened under.

Open role fit, open Decision-Ready Contact for first-contact context, or open PDF resume after the contact context is clear.

Current Proof Foundation

  • Autoschool Intake/Admin work sample: first-job backend/internal-tools signal with Telegram request intake, backend validation, database record, admin queue handoff, operator status workflow, and synthetic-only public evidence.
  • DriveDesk AI Operator route: fastest route for role fit, proof, and contact.
  • Decision-Ready Contact: initial contact route before the PDF resume handoff.
  • DriveDesk AI Operator: main AI sales/support workflow case proof.
  • Skill Evidence: skills mapped to public repositories, docs, demos, CI, and runtime evidence.
  • AI Ops Workflow Kit: reviewable FastAPI AI/RAG workflow backend evidence with document/CRM/call intake, first-slice playbook, privacy redaction before RAG/approval/CRM handoff, deterministic RAG quality eval, transcript analysis, Telegram approvals, dry-run Bitrix CRM handoff, idempotent outbox, reviewer acceptance report, production-readiness drill, Docker, and n8n boundaries.
  • AI workflow evidence and RAG workflow evidence are visible as backend/integration differentiators, not the first title I need to be screened under.
  • AI Automation Role Fit: backend-owned AI workflow boundaries, approval flow, CRM handoff, and production-readiness evaluation.
  • DriveDesk Core: backend structure, public demo, CI, docs, and adapter boundaries.
  • DeployMate: deployment, release gates, health checks, runbooks, and recovery discipline.

Good First Context

  • Role or project surface.
  • Remote setup and expected ownership.
  • Stack or systems involved.
  • Current workflow or technical pain.
  • What should improve first.
  • Timeline, deadline, or first-month success condition.