Artificial Intelligence Engineer

Role Overview

Were hiring an AI Engineer who is a problem-solver first : someone who can ship , debug , and iterate fast . Youll help build the core AI workflows powering our tutoring productespecially 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 wont fit. If you like building real systems end-to-end and seeing your work hit production quickly, youll 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 youve 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.

What We're Looking For (Must Have Signals)

Core Engineering

• 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).

AI Engineering Readiness

• 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.
• Youve built something real : internships, substantial course projects, shipped side projects, research engineering, or open-source contributions.

Pedigree / proof of work (we care about evidence, not labels)

• 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).

How You Work (This Matters)

Youll do well here if you:

• Default to ownership: you dont 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.

Why Join Fermi?

• 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 impactyour code ships and matters.
• Work with a team that cares about craft, not just hype.

Self-Selection: Please Dont Apply If

You want remote/hybrid (this is onsite Bangalore only).

You prefer narrow tickets and minimal ambiguity.

Youre not excited about production engineering (monitoring, reliability, cost, latency).

Youre mainly looking for a research-only role.