Backend-Owned AI Workflow
RAG, transcript/call/document analysis, approval flow, CRM action, operator workflow, citations, quality checks, and audit trail.
LinkedIn Services fit
Broad service labels, narrow engineering ownership.
LinkedIn may route requests through broad labels such as Cloud Application Development, Web Development, Application Development, Custom Software Development, Information Management, or IT Consulting. I treat those labels as a fit only when the work has backend/platform, AI workflow, integration, data, DevOps, or internal-operations ownership.
The actual offer is concrete: turn one messy business workflow into a backend-owned system with records, state, adapter contracts, logs, tests, docs, deployment/recovery path, and a handoff route.
Best-Fit Service Requests
CRM / ERP / API Integration
Explicit source/target contracts, mapping, validation, retries, idempotency, logs, rollout notes, and recovery path.
Internal Operations Platform
FastAPI/PostgreSQL backend, admin records, roles, workflow state, outbox, tests, Docker, CI, docs, and runbook.
DevOps / Recovery Sprint
Deploy path, health checks, smoke checks, logs, backup/restore, rollback thinking, release gates, and operator handoff.
Data Workflow
Repeatable ingestion, validation, reporting, review, approval, and system handoff instead of spreadsheet-only output.
Workflow Teardown
Risk map, system boundary, smallest responsible working slice, proof route, and next implementation step.
Not The Right Request
Not my target right now unless there is a real backend or integration system to own:
- isolated website refresh;
- student or course assignment;
- standalone game clone;
- generic mobile or ecommerce app;
- vague request with no system boundary and no verifiable success condition.
Useful First Context
- Business process and current tools.
- Systems, data sources, APIs, documents, transcripts, CRM objects, or chats involved.
- One success condition and what must not break.
- Deadline, timebox, access limits, hosting constraints, and handoff depth when relevant.
What I Can Send Back
- Fit read against backend/platform, AI workflow, integration, data, DevOps, and operations ownership.
- Smallest responsible working slice.
- Risk check for missing information, fragile assumptions, access, data, and integration boundaries.
- Proof route through repo, CI run, live page, doc, demo, or PDF resume path.
- Handoff route through tests, logs, docs, runbook, smoke check, deployment note, or support boundary.