Full-Stack AI Engineer

360 Labs

Bengaluru

On-site

INR 3,000,000 - 5,500,000

Full time

18 hours ago
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Job summary

360Labs is a fast-growing AI company delivering end-to-end AI products across government, health, fintech and more. We seek an engineer who can ship product across data, model, backend, frontend and deployment, driving real-world impact.

You’ll build and ship features end to end, train and distil models, create robust evaluations, and deploy LLM systems in production. You’ll work autonomously in a small, fast-moving team with a strong emphasis on quality and cost.

Qualifications

  • Ship real products, not notebooks.
  • Strong experience with Python & TypeScript and modern web stacks.
  • Hands-on with LLMs, RAG, agents, and evaluation methods.

Responsibilities

  • Ship full-stack features from data pipelines to user interfaces.
  • Train, fine-tune and distil models for production use.
  • Build evaluations and measurable quality metrics for models.
  • Design and deploy LLM systems with production-grade orchestration.
  • Monitor latency, cost and failures; fix root causes.
  • Write clean, well-tested code that others can extend.

Skills

Python
TypeScript
Web frameworks
Databases
Cloud infrastructure
LLMs
RAG
Agents
Evaluation

Tools

LLM tooling

Job description

360Labs is among Asia's fastest growing AI companies. We build AI agents, enterprise software and products for clients across government, defence, healthcare, fintech and beyond, and we ship fast: working prototypes in days, production systems in weeks. We're looking for an engineer who can take an idea and ship it as a working product, covering data, model, backend, frontend and deployment.

What You'll Do

  • Ship across the full stack. Build and ship product features end to end, from data pipelines and APIs to the interface the user actually touches. You'll own features, not tickets.
  • Train, fine-tune and distil models. Adapt models for specific tasks, then make them smaller, faster and cheaper with no loss in quality. Know when a fine-tuned small model beats a frontier API call, and prove it.
  • Build evaluations. Create evaluation sets and pipelines so we measure quality instead of guessing at it. Every model change should come with numbers.
  • Build LLM systems for production. Design and build RAG pipelines, tool use, agents and structured outputs that hold up with real users and real data, not just in a demo.
  • Run what you ship. Put models into production, monitor latency, cost and failures, and fix problems at the root cause rather than patching symptoms.
  • Write code others can build on. Write clean, tested code that other engineers can read, test and change without needing to ask you first.

About You

  • You are an engineer who has shipped real products, not just notebooks. You're comfortable across Python and TypeScript, modern web frameworks, databases and cloud infrastructure.
  • You have hands-on experience building with LLMs, whether that's RAG, agents, fine-tuning or evaluation, and you understand where they fail as well as where they shine.
  • You are AI-native. You use AI coding tools every day, you know how to get the most out of them, and you still understand and own every line you ship.
  • You care about quality and cost. You think about latency, token spend and failure modes before they become someone else's problem.
  • You are reliable and proactive. You deliver what you said you would, flag problems early, and don't wait to be told what to fix next.
  • You are happy working with autonomy in a small, fast-moving team, and confident asking for help when you need it.

We especially want to hear from you if you have

  • Experience fine-tuning, distilling or quantising models and deploying them in production.
  • Built evaluation frameworks or LLM observability tooling.
  • Worked on client-facing projects at a startup, product studio or consultancy.
  • Open-source contributions, research or side projects you're proud of. Send us the link.
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