Ismail Valiev — AI Engineer
I build LLM systems that don't fall apart in production.
Summary
I'm a Technical Lead and Applied AI Engineer. I build AI platforms for production — not labs, not demos, actual enterprise systems under real load.
LLMs are non-deterministic by nature. Controlling that chaos is where the real expertise is — and it comes down to four things:
- retrieval that finds the right context, even in messy data
- evaluation that catches failures before users do
- fallbacks that degrade gracefully instead of silently breaking
- observability that tells you what actually happened
The model is often the easy part.
What I do
- Lead engineering teams building AI platforms for enterprise clients
- Define architecture and own the hard calls — so the team doesn't get stuck on them
- Teach engineers how to think about retrieval, evaluation, and failure in LLM systems
- Set standards for reliability that the team can actually apply
- Make the trade-offs between latency, cost, and quality — and explain why
- Help organisations adopt AI without burning down what already works
Current focus
- Getting agentic systems from PoC to production
- Evaluation and observability for LLM systems
- Technical leadership in applied AI