Cloud Infrastructure Engineer - LLM Routing & Cost Optimization

We're looking for someone genuinely strong on **Google Cloud Platform** \- not necessarily years of work experience, but real depth: you've built things on GCP, you understand its IAM, quota, and networking model cold, and you can reason about Cloud Run, Vertex AI, and multi\-project setups from first principles. You'll design and build Zeqo's **multi\-provider LLM router** \- the internal system that decides which model/provider handles each request (Google Gemini, OpenAI, Anthropic, and self\-hosted open\-weight models), optimizes for cost/latency/quality, and aggressively reduces redundant token spend through prompt caching and smart request management. This is a foundational infrastructure role: get it right and every downstream product gets faster and cheaper automatically.

This is intentionally open to early\-career engineers — we care far more about depth of GCP knowledge and evidence of things you've actually built than a resume with years on it.

• **Location: Fully Remote***

What You'll Do

• **Design and build a unified LLM router** that abstracts Google, OpenAI, Anthropic, and self\-hosted model endpoints behind a single internal API, so product teams never hardcode a provider.
• **Implement intelligent routing logic** — route by task type, cost ceiling, latency budget, context length, or model capability (e.g., OCR evaluation vs. conversational tutoring vs. embedding generation).
• **Build fallback and failover chains** so a rate limit, timeout, or outage on one provider automatically retries on another without breaking the user experience.
• **Design prompt/response caching** (semantic and exact\-match) to cut redundant token usage and reduce rate\-limit pressure — particularly for repeated question\-bank queries, common doubt patterns in Mophy, and OCR grading rubrics.
• **Own rate\-limit and quota management** across providers and GCP projects, including request queuing, backpressure, and graceful degradation under load.
• **Build cost observability**: per\-request cost attribution, per\-product/per\-school cost dashboards, and alerting on spend anomalies.
• **Benchmark providers and models** on cost, latency, and quality for Zeqo's specific workloads (OCR grading, RAG retrieval via Mophy, test generation) and recommend routing policy changes.
• **Collaborate with the ML/infra work already in flight** — our self\-hosted BGE\-large\-en\-v1\.5 embedding service on Cloud Run, GCP multi\-project quota isolation, and DPO training data pipelines — and integrate the router cleanly into that architecture.

What We're Looking For

• **0–2 years of experience** — this is deliberately open to freshers and early\-career engineers. What matters is depth, not tenure.
• **Real GCP depth**, demonstrated through projects, coursework, certifications, or personal builds: Cloud Run, IAM, service accounts, multi\-project/quota architecture, Vertex AI. A GCP certification (Associate Cloud Engineer or Professional Cloud Architect) is a strong plus but not required if you can show equivalent hands\-on work.
• Solid backend fundamentals — API design, working with external APIs, basic distributed\-systems thinking (retries, timeouts, rate limits).
• Comfort with or eagerness to learn caching strategies (Redis or similar); exposure to LLM APIs (OpenAI, Gemini, Anthropic) is a plus but not a hard requirement — we'll teach you the LLM\-specific parts.
• A cost\-conscious, first\-principles mindset — you enjoy understanding *why* a system is expensive or slow, not just making it work.
• Startup mindset: comfortable figuring things out with a small team, moving fast, and owning a system end\-to\-end even without a large playbook to follow.
• Bonus: personal projects or coursework touching RAG, embeddings, or prompt engineering.

To Apply

Send your resume and any GCP\-related projects (GitHub, coursework, certifications, personal builds — anything that shows depth) to **hello@zeqo.in** or WhatsApp **\+91\-9136734595**. We'd rather see a GCP project you built and can explain in detail than a polished resume with no substance behind it.

Along with your resume, please answer these three questions

• **Describe a GCP project or setup you've built (personal, academic, or professional).** What service(s) did you use, and what was the trickiest problem you had to solve?
• **If an API you're calling suddenly starts rate\-limiting you mid\-request, what's your first instinct for handling it?** (No wrong answers — we want to see how you think about this.)
• **What's one thing about cloud costs (GCP or otherwise) that you think most engineers get wrong or don't think about enough?**

Pay: ₹20,000\.00 \- ₹35,000\.00 per month

Benefits

• Flexible schedule
• Work from home

Work Location: Remote