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Principal backend and AI platform engineer building reliable systems for applied AI, operational workflows, and real-world data infrastructure.

Peter Jasko

Professional context

I build backend systems for operational software: APIs, data pipelines, search, event-driven workflows, and applied AI platforms that need to behave reliably in production.

My recent work sits at the intersection of distributed systems and AI product engineering: LangGraph agents, RAG, text-to-SQL, streaming UX, evaluation tooling, observability, and workflow automation. Before that, I spent years building commerce and logistics infrastructure across order search, shipping, inventory allocation, integrations, and high-volume data movement.

Focus Applied AI platforms

Mode Backend / distributed systems

Surface Resume / writing / contact

01

Systems

Production systems for applied AI

I care about the backend work that makes AI products usable: clear APIs, durable state, resumable workflows, traceable runs, predictable latency, and infrastructure that keeps working after the demo.

02

Interfaces

Interfaces for messy operations

The systems I like most sit close to real work: warehouse flows, ecommerce operations, customer support, logistics, search, and internal tools. Good software should make complex state legible without making users understand the machinery underneath.

03

Writing

Notes from implementation

I use the blog and lab sections for practical notes: AI platform patterns, agent workflows, evals, backend architecture, reliability lessons, and small experiments that are useful enough to revisit.