Target: remote-capable Junior Python Backend / API Automation. Adjacent lanes: QA/API Python, CRM/API Integration, Internal Tools, and Support Engineer with Python when the work is backend/API-heavy.
Experience base: Autoschool54 / DriveDesk backend and application-support work since March 2024, turned into public-safe work samples without exposing live production data; private production data replaced by synthetic evidence.
First code proof: OpsDesk Reviewer Replay proves synthetic webhook intake, duplicate idempotency, operator queue, status handoff, outbox dispatch, metrics, support diagnostics, and OpenAPI checks without local Docker. Real-work context: DriveDesk Business Intake API Handoff maps bot-style intake -> backend validation/FastAPI preview -> validated business record -> admin queue -> status transition -> outbox/integration handoff -> pytest/API smoke/CI with synthetic public data.
First useful result: one FastAPI endpoint, data model, admin queue step, API/CRM mapping, pytest/API smoke check, SQL/data check, or runbook gap shipped as a reviewed slice with docs and handoff notes.
I build Python backend/API automation for messy business workflows: FastAPI/PostgreSQL services, admin queues, REST/OpenAPI boundaries, API/CRM integrations, QA/API checks, and handoff docs. DriveDesk and RAG/AI workflow evidence stay visible only after the backend/API fit is clear.
Delivery boundary: the useful signal is a reviewed FastAPI/PostgreSQL/Telegram/admin slice with tests, logs, docs, and handoff. Stack fit: Python, FastAPI, PostgreSQL, REST/OpenAPI, SQL, pytest/API smoke checks, Docker/Compose boundaries, GitHub Actions, docs, runbooks, and recovery notes.
| Open first | Decision signal |
|---|---|
| OpsDesk Reviewer Replay | Fastest code proof: no-Docker synthetic replay for webhook intake, idempotency, operator queue, status handoff, outbox dispatch, metrics, support diagnostics, OpenAPI checks, CI, and privacy audit. |
| DriveDesk Business Intake API Handoff | Real-work public-safe route: bot-style intake -> FastAPI endpoint -> admin queue -> status transition -> outbox/integration handoff, with OpenAPI/tests/CI and no private production data. |
| GitHub recruiter handoff | GitHub-native 30-second wrapper: target role, first proof, PDF, markdown work samples, recruiter prompt, and privacy boundary. |
| Hiring Decision | 30-second yes/no screen for first role lane, first safe task, and no-fit boundaries. |
| LinkedIn Recruiter Packet | 30-second role lane, first work sample, scope boundary, and recruiter prompt. |
| First Backend Role Fit | The practical first-job question: what can a team safely give me first? |
| Autoschool Intake/Admin work sample | Public-safe first proof for intake -> validation -> database record -> admin queue -> operator status. |
Forwarding after fit is clear: Recruiter review pack, PDF resume, and ATS plain-text resume. For application parsers, vacancy-specific routing, and first messages: Role Fit Message Examples. Deeper technical review: DriveDesk AI Operator and AI Backend Review Pack.
Message me first when there is one messy workflow, one risky integration boundary, or one Python/backend automation, API/CRM, QA/API, AI-assisted workflow, or support-diagnostics slice that should become testable, logged, documented, and handed off.
First reply promise: I will answer with a fit read, risky assumptions, the smallest responsible first slice, the work sample to inspect, and the right next path: remote-capable role screen, technical review, scoped project, or no-fit.
Suggested recruiter path: GitHub recruiter handoff -> OpsDesk Reviewer Replay -> DriveDesk Business Intake API Handoff -> LinkedIn Recruiter Packet -> First Backend Role Fit -> Autoschool Intake/Admin work sample -> PDF resume. Use the recruiter review pack only after the role fit is clear. Message on LinkedIn with the role title and one useful success condition; remote setup, stack/systems, timeline, and compensation band can follow after fit is clear.
LinkedIn support routes: LinkedIn Profile Signal for headline, About, Featured, Open-to-Work, and skills alignment; Backend/API Work Samples for the profile-view work-sample route; Recruiter Preferences for Open-to-Work filters; Decision-Ready Contact for first-contact context; and Skill Evidence for the skill-to-work-sample map.
AI-assisted engineering workflow: I use AI tooling to move faster through discovery, implementation, debugging, docs, and review, while data boundaries, privacy checks, tests, logs, Docker/CI handoff, runbooks, and shipped quality stay reviewable.
Search-fit titles: Junior Backend Developer, Junior Python Developer, Python Automation Engineer, Backend Automation Engineer, QA Automation Python, API Testing / Test Automation Engineer, Support Engineer with Python, Integration Engineer, CRM/API Integration Engineer, and Internal Tools Engineer.
LinkedIn recruiter search alignment: remote-capable or Russian-speaking full-time roles where Python, FastAPI, PostgreSQL, Docker, GitHub Actions, RAG, Vector Databases, CRM/ERP/API integration, QA Automation Python, OpenAPI, n8n, Telegram, or pgvector appear in the role.
Best immediate starts: Python/backend workflow slice, CRM/ERP/API adapter, internal operations tool, QA/API verification path, or Docker/CI handoff. AI workflow automation is a differentiator after backend/API fit is established.
| Send me | Best match | Fast review |
|---|---|---|
| Remote-capable full-time role | Junior Python backend, QA/API automation, integrations, internal tools, Python/FastAPI/PostgreSQL, Docker/CI handoff. | Hiring Decision, Decision-Ready Contact, LinkedIn Recruiter Packet, First Backend Role Fit, DriveDesk Business Intake API Handoff, Autoschool Intake/Admin work sample, PDF resume |
| Technical review | Code, CI, live smoke, runtime boundaries, privacy redaction, adapter contracts, runbooks, and public-safe evidence. | Verification pack, AI Ops evidence status |
| Scoped project after role fit | One messy workflow, one success condition, and a working slice with tests, logs, docs, and handoff path. | Work with me, fixed-scope offers, Start conversation |
DriveDesk AI Operator is deeper backend/AI workflow evidence after the first-role backend/API fit is clear: documents, call audio, transcripts, or CRM leads -> RAG, analysis, scoring, tasks, Telegram approval, and CRM handoff. Broader DriveDesk material stays in deeper review, not the first screen.
Since March 2024, I have supported Autoschool54 backend/application-support work remotely while turning real operational problems into public-safe backend workflow samples. Key pinned repos: OpsDesk Reviewer Replay, DriveDesk Core, AI Ops Workflow Kit with business scenario replay, first-slice playbook, and live PostgreSQL/pgvector persistence, and MPlusForm.
| Need | Review surface |
|---|---|
| Backend/API workflow | FastAPI/PostgreSQL backend, admin queue, REST/OpenAPI, idempotent outbox, SQL metrics/data checks, tests, docs, and handoff. |
| CRM/ERP/API integration | Explicit adapters, mappings, retries, logs, idempotency, rollout notes, and recovery path. |
| QA/API verification | Python, pytest, REST/OpenAPI checks, reproducible issue notes, smoke checks, and pass/fail evidence. |
| Docker/CI handoff | Docker, CI/release gates, health checks, logs, backups, smoke checks, and rollback procedure. |
Fast fit checklist: message me when the work is remote-capable or async-reviewed and needs a backend/API workflow, CRM/ERP/API integration, internal operations tool, QA/API verification path, Docker/CI handoff, or one first working slice with tests, logs, docs, and a handoff route. I am not positioning for onsite-only roles, pure prompt/content tasks, isolated static websites, student/course assignments, standalone game clones, generic mobile/ecommerce apps without a backend/integration review path, or vague work where success cannot be defined.
LinkedIn: linkedin.com/in/alex-gerlitz-a659ab3bb · LinkedIn Services