AI Integration Engineer — LLM features shipped into live SaaS products

I am an AI Integration Engineer focused on turning LLM capabilities into reliable features inside real SaaS products.

My focus areas include LLM feature integration, retrieval and RAG workflows, backend and API integration, practical evaluation, observability, failure handling, latency, and cost control. My preferred approach starts with the user workflow and clear acceptance criteria, then reduces the work to a focused technical milestone.

I value honest engineering decisions over impressive demos. That includes identifying where deterministic software is safer or more economical than an LLM, making uncertainty visible, and designing integrations that remain maintainable after the prototype stage.

Typical ways I can help:
• Scope an AI feature and identify the highest-risk assumptions
• Integrate an LLM capability into an existing SaaS workflow
• Review or improve a retrieval/RAG pipeline
• Define practical evaluation criteria and test cases
• Move a prototype toward a production-ready milestone

For initial communication and scheduling, I use an AI-assisted operations workflow. Technical commitments, final scope, and acceptance criteria are confirmed directly before work begins.

Work Terms

Hourly rate: $70. Small discovery or implementation milestones can start at $250 when the scope is suitable.

I prefer written scope, acceptance criteria, and milestone deliverables before implementation begins. Communication is primarily asynchronous in writing, with calls scheduled when they materially improve alignment. Availability and delivery dates are confirmed for each engagement.

Payments and funded milestones should use Guru SafePay. Any change in scope, timeline, or deliverables should be agreed in writing before the additional work starts.