Founding Engineer - Olympiz

An AI-first EdTech company building next-generation learning solutions for JEE, NEET, Olympiads, and school-level competitive preparation. A platform where teachers and students connect for live classes offline and online. Target Audience: Students preparing for JEE, NEET, Olympiads, and school-level competitive exams. Core Framework: Operating at the intersection of education, live teaching sessions, AI, product, content, student mentoring, testing, analytics, and growth. The Goal: To create a unified platform that makes high-quality academic guidance significantly more personalized, scalable, and outcome-driven

You'll own the systems that make an autonomous agent trustworthy in production. This is not just prompt engineering, and it's not model training - it's that and all the engineering layers in between: model steering, memory architecture, orchestration design, latency optimization, deterministic vs non-deterministic systems tradeoff, deployment, and operator tooling.

Concretely, the kind of work you'd have done here last week would include enhancing agent memory systems, runtime and scheduling reliability and predictability, adding new capability and tools to deployed agents, operator tools, live system debugging and benchmarking various models for price, latency and quality. And that is just last week. We are a small nimble startup rapidly working to address customer needs in this growing space, so things change rapidly.

5+ years of software engineering, with real production ownership of distributed or stateful systems - you've been paged for something you built and made it not happen again.

Strong understanding of LLM based native app building, combining classic and model driven applications to get the best of both. You've built on LLMs beyond demos: agent frameworks, tool use, context management, eval fixtures, and you know why "it worked in the transcript" isn't evidence.