Alex Gerlitz Python Backend / API Automation | FastAPI | PostgreSQL | CRM Integrations LinkedIn: linkedin.com/in/alex-gerlitz-a659ab3bb GitHub: github.com/AlexGerlitz Portfolio: alexgerlitz.github.io/AlexGerlitz Recruiter packet: alexgerlitz.github.io/AlexGerlitz/linkedin-recruiter-packet.html PDF resume: alexgerlitz.github.io/AlexGerlitz/output/pdf/alex-gerlitz-python-backend-automation-resume.pdf 30-SECOND SHORTLIST Target role: remote Junior Python Backend / API Automation. Adjacent lanes: QA/API Python, CRM/API Integration, API Testing / Test Automation Engineer, Internal Tools, and Support Engineer with Python when the role is backend/API-heavy. Experience basis: remote Autoschool54 / DriveDesk backend and application-support work since March 2024. Best first assignment: one backend/API slice with clear input, output, validation rule, admin or reviewer surface, smoke/evidence check, and handoff note. First proof route: Autoschool Intake/Admin work sample. Contact route: Decision-Ready Contact. FIRST-MONTH STARTS - Python backend: FastAPI endpoint, data model, validation rule, admin queue step, documentation, and evidence check. - QA/API Python: pytest, REST/OpenAPI checks, SQL/data checks, smoke routes, reproducible issue notes, and log review. - Integration/API: CRM/API mapping, adapter boundary, webhook or Telegram workflow, retries, audit log, and handoff note. - Application support with Python: ticket triage, log analysis, SQL/data check, small automation fix, documentation, and repeatable verification. CURRENT EXPERIENCE Python Backend & Application Support Engineer Autoschool54 / DriveDesk backend/internal-tools work Remote, March 2024 - Present - Support live admin/operator workflows: Telegram intake, API/CRM-style handoff, SQL/data checks, documents, schedules, payments, accounts, access, and troubleshooting. - Translate unclear business requests into small technical actions, repeatable workflows, documentation, privacy boundaries, and recovery paths. - Build and support backend/internal-tools slices around request intake, backend validation, database records, admin queues, operator status, logs, and handoff notes. - Use AI tooling for domain research, implementation options, debugging, tests, docs, and review while verifying outputs through inspection, tests or smoke checks, logs, comparison, and written notes. PUBLIC WORK SAMPLES Autoschool Intake/Admin work sample alexgerlitz.github.io/AlexGerlitz/autoschool-intake-admin.html Synthetic public evidence of Telegram request intake -> backend validation -> database record -> admin queue -> operator status workflow. This is the first work sample to inspect for junior backend, internal tools, QA/API, and support-with-Python screens. First Backend Role Fit alexgerlitz.github.io/AlexGerlitz/first-backend-role.html Practical first-job route: what a team can safely give me first, how I would reduce risk, and which public work sample proves the fit. DriveDesk AI Operator alexgerlitz.github.io/AlexGerlitz/drivedesk-ai-operator.html Backend-owned AI workflow: document/transcript/CRM lead intake, RAG, call-analysis JSON, Telegram approval, audit, retries, and CRM handoff. AI Ops Workflow Kit github.com/AlexGerlitz/ai-ops-workflow-kit Reviewable FastAPI/PostgreSQL/pgvector backend evidence with privacy redaction, approvals, idempotent outbox, transcript analysis, dry-run CRM handoff, Docker, CI, and smoke checks. DriveDesk Core github.com/AlexGerlitz/drivedesk-core FastAPI/PostgreSQL backend foundation: tenants, RBAC, audit/outbox, workers, adapter boundaries, OpenAPI, CI, docs, and public demo. SKILL EVIDENCE Backend/API automation: Python, FastAPI, PostgreSQL, SQL, REST/OpenAPI, OpenAPI, pytest, data models, admin queues, validation, docs, and handoff. QA/API support lane: QA Automation Python, API Testing, Test Automation Engineer, pytest, REST/OpenAPI checks, SQL/data checks, smoke routes, issue notes, and log analysis. Integrations: Telegram, CRM/ERP/API adapters, workflow integration, webhooks, retries, audit logs, mapping, validation, and adapter contracts. AI workflow automation: RAG/transcript/ticket/lead flows with human approval, privacy redaction, PostgreSQL/pgvector, reviewable outputs, and backend state. Reliability handoff: Docker Compose, GitHub Actions, health checks, smoke checks, logs, runbooks, English technical documentation, backup notes, and recovery notes. SEARCH-MATCH STACK Core stack: Python, FastAPI, PostgreSQL, SQL, REST/OpenAPI, OpenAPI, pytest, Docker Compose, GitHub Actions. Proof-backed differentiators: AI/RAG workflow evidence, Telegram workflows, CRM/API integration, PostgreSQL/pgvector, adapter contracts, audit logs, retries, and human approval flows. Market-fit lanes: Junior Python Backend, Back End Developer, Junior Backend Developer, Python Developer, QA Automation Python, Quality Assurance Automation Engineer, API Testing / Test Automation Engineer, Integration Engineer, CRM/API Integration, Internal Tools, and Support Engineer with Python when the role is backend/API-heavy. Support/QA keywords: technical support, application support, ticket triage, bug reports, test cases, log analysis, SQL/data checks, reproducible issue context, and Git-based handoff notes for backend/API workflows. Boundary: Docker/CI is handoff and reliability evidence, not a senior DevOps, Kubernetes, Terraform, or platform ownership claim. Responsible AI use: AI speeds up implementation, debugging, documentation, and review; architecture, privacy, verification, logs, docs, and product boundaries stay mine. EVIDENCE BOUNDARY Public samples use synthetic or redacted evidence only: no real names, phone numbers, chat IDs, admin URLs, logs, dumps, tokens, credentials, or live admin screenshots. The strongest technical review path is LinkedIn Recruiter Packet -> First Backend Role Fit -> Autoschool Intake/Admin work sample -> Skill Evidence -> Verification Pack. EDUCATION Novosibirsk State Technical University (NSTU) - Applied Informatics, 2025 - Present.