An AI integration developer is not a generic "AI person." The job is to add AI into an existing product safely: APIs, UI surfaces, retrieval, tools, review, and cost controls. Use this skills checklist before you hire.
1. Core LLM integration skills
- OpenAI and Claude SDKs with production error handling
- Streaming responses to product UIs
- Structured outputs / JSON schema validation
- Prompt versioning and rollback thinking
- Moderation and basic abuse handling
2. Retrieval and knowledge skills
- Document ingestion and chunking choices
- Embeddings and vector store selection (pgvector vs managed)
- Citation and fallback when retrieval is weak
- Refresh strategy when docs change
3. Product feature skills
- Chatbots with history, auth, and handoff
- Assistive GenAI features (drafts, summaries) with review
- Agents with tool contracts and human approval
- Feature flags and shadow mode for risky launches
4. Stack bridge skills
- Laravel or Node service boundaries for LLM calls
- Queues/jobs for long AI work
- React/Next streaming chat UX
- Optional FastAPI sidecar when Python tooling helps
5. Operability skills
- Token metering and budget alerts
- Logging without leaking PII or secrets
- Golden-set evaluation for regressions
- Incident habits when the model provider has an outage
6. Soft skills that show up in delivery
- Can say no to agent hype when a form + prompt is enough
- Writes clear tradeoffs for build vs buy
- Communicates risk to non-technical founders
7. How to test the skills quickly
Ask for a short paid task: integrate a structured extraction endpoint into a sample Laravel or Node app, or build a tiny RAG over five markdown files with citations. Review code clarity and failure modes more than prose about AI trends.
Summary
Hire an AI integration developer for product wiring, not for research theater. The checklist above is the minimum bar for SaaS teams.
Related pages: AI Integration Services, Hire AI Developer, OpenAI API Development.
Prakash Tank
Full-Stack Architect & Tech Enthusiast. Passionate about building scalable applications and sharing knowledge with the community.
