AI Engineer

About Fermi

Fermi is an early-stage AI tutoring startup, an initiative of Meraki Labs, dedicated to revolutionizing education globally. Our mission is to democratize world-class tutoring by making it accessible to every student through advanced AI. We are a dynamic and lean team of educators, designers, and engineers, united by a strong conviction that thoughtful design and cutting-edge AI can profoundly transform the learning experience.

Led by experienced founders, including Mukesh Bansal (Founder – Myntra, CureFit, Nurix) and Peeyush Ranjan (VP-Google, CTO-Flipkart, Airbnb), we are building a product that aims to reshape how millions of students learn—turning academic challenges into accomplishments. We operate out of Bangalore, India, fostering a high-velocity environment that prioritizes impact, ownership, and direct collaboration to define and build the future of AI in education.

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 tutoring product—especially agentic tutoring systems—and harden them into production-grade, scalable, observable systems.

This role is intentionally not for everyone. If you want 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.

What You’ll Do

• Build and ship core AI workflows for our tutoring app:
• agentic tutoring flows (hinting, step-by-step guidance, misconception detection)
• answer evaluation / grading and feedback loops
• retrieval + grounding (content ingestion, chunking, embedding, re-ranking)
• personalization (student memory, progress signals, difficulty adaptation)
• multimodal pipelines (images/diagrams; bonus if you’ve touched voice)
• Turn prototypes into robust production systems:
• latency + cost optimization (caching, batching, streaming, fallbacks)
• eval-driven iteration (offline test sets, regression checks, quality gates)
• observability (traces, logs, metrics, prompt/version tracking)
• reliability + safety (guardrails, refusal behavior, policy/age-appropriate output)
• Own features end-to-end:
• from rough PRD → implementation → deployment → monitoring → iteration
• Collaborate closely with product/design/education to translate learning goals into AI behavior.
  
  

• 1 to 5 years of strong Python fundamentals; you can write clean code and also “hack” when needed.
• Comfortable building services with FastAPI/Flask, writing APIs, and debugging production issues.
• Practical understanding of Docker, local dev workflows, and basic deployment concepts.
• Good CS foundations (data structures, basic systems thinking, debugging).
  
  

• Hands-on experience with at least one:
• OpenAI SDK (or similar), LangChain, Haystack (or comparable LLM framework)
• You understand the difference between:
• prompting vs tooling vs retrieval vs agents vs evals
• You’ve built something real:
• internships, substantial course projects, shipped side projects, research engineering, or open-source contributions.
  

• CS background preferred (or equivalent demonstrated capability).
• Strong signal from top engineering programs in India or an equivalent track record (exceptional projects / OSS / internships that clearly show you can perform).
  
  

• default to ownership: you don’t wait to be told every step
• can move fast without being sloppy
• enjoy ambiguity and turn it into clear execution
• treat quality as an engineering problem: tests, evals, instrumentation, iteration
  
  

• Build core AI product (not demos) that students use daily.
• Massive scope for learning: agents, evals, multimodal tutoring, production hardening.
• Small team, high trust, direct impact—your code ships and matters.
• Work with a team that cares about craft, not just hype.
  
  

• You want remote/hybrid (this is onsite Bangalore only).
• You prefer narrow tickets and minimal ambiguity.
• You’re not excited about production engineering (monitoring, reliability, cost, latency).
• You’re mainly looking for a “research-only” role.