Meraki Labs
Engineering
AIEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“AI Engineer at Meraki Labs. Skills: AI Engineering, Production Engineering, LLM Frameworks. Ship AI workflows. Debug AI workflows”
What You'll Achieve.
Ship things fast; See work hit production quickly
Industry & Context.
Problem-solver
What They're Looking For.
Must Have
5 to 10 years of Python, 5 to 10 years of Java, 5 to 10 years of Node.js, Using LLMs to generate code, Building services with FastAPI, Building services with Flask, Writing APIs, Debugging production issues, Practical understanding of Docker, Local dev workflows, Basic deployment concepts, Hands-on experience with OpenAI SDK, Hands-on experience with LangChain, Hands-on experience with Haystack, Understanding prompting, Understanding tooling, Understanding retrieval, Understanding agents, Understanding evals
Nice to Have
Familiarity with book/content metadata, Familiarity with EPUB/PDF parsing, Familiarity with semantic search
What You'll Do.
Build production-grade systems
Build scalable systems
Build observable systems
Implement observability
Implement refusal behaviour
Implement content policy
Translate goals into AI behaviour
How You'll Work.
Team & Collaboration
Collaborate with product; Collaborate with design
Full Job Description
About Meraki Labs: Meraki Labs is a startup incubation centre founded by Mukesh Bansal — the builder behind Myntra, Curefit, and Nurix AI. We identify breakthrough ideas across technology, health, commerce, education, and AI, and build them into companies from the ground up. Our engineering foundation is led by Peeyush Ranjan — formerly VP at Google, VP of Engineering at Airbnb, and CTO at Flipkart — bringing world-class product and technical depth to every venture we back. Role Overview We’re hiring an AI Engineer who is a problem-solver first: someone who can ship, debug, and iterate fast. You’ll help build the core AI workflows powering our products and harden them into production-grade, scalable, observable systems. This role is intentionally not for everyone. If you want a tight scope, predictable tasks, or “only research / only backend,” this won’t fit. If you like building real systems end-to-end and seeing your work hit production quickly, you’ll love it. Production Engineering • Latency & cost optimisation — caching, batching, streaming, fallbacks • Observability — traces, logs, metrics, prompt and version tracking • Reliability & safety — guardrails, refusal behaviour, age-appropriate content policy End-to-End Ownership • Drive features from rough PRD through implementation, deployment, monitoring, and iteration • Collaborate closely with product and design to translate reading goals into AI behaviour What We Are Looking For • 5 to 10 years of strong Python, Java, or Node.js etc fundamentals and using LLMs to generate code and ship things fast • Comfortable building services with FastAPI / Flask, writing APIs, and debugging production issues • Practical understanding of Docker, local dev workflows, and basic deployment concepts • Hands-on experience with at least one of: OpenAI SDK (or similar), LangChain, Haystack, or a comparable LLM framework • You understand the practical difference between prompting, tooling, retrieval, agents, and evals • Familiarity
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