AI Engineer Intern

Abstrabit Technologies Private Limited; Bengaluru; On-site; INR 167,000 - 279,000; Part time

Job summary

Abstrabit Technologies Private Limited in Bengaluru invites interns who are strong in any one of four AI layers: LLMOps, Enterprise RAG, model fine-tuning, or AI agents and workflows. You will pick your strongest area, work directly with the founders and senior engineers, and build real systems end-to-end.

Prior projects, open-source contributions, and competition exposure are valued, with a bias toward tangible deliverables.

Qualifications

• Proof of good work in your chosen area or a project you built and can demo.
• Open source contributions or Kaggle/GSoC/hackathons show your skills.
• Strong documentation and the ability to explain technical work clearly.
• Public and verifiable work matters more than college CGPA.

Responsibilities

• Build and ship working systems, not slide decks.
• Own your work end to end: design, build, benchmark, document.
• Work directly with the founders and senior engineers.
• Go deep in your layer while getting exposure to the other three.

Skills

LLMOps

RAG

Fine-tuning

Kubernetes

Tools

Kubernetes

Job description

Location: Bengaluru, Interviews for this position will be conducted in person at our Bengaluru office.

Type: Internship

Experience: 0 - 1 year

About Us

Abstrabit is a private AI company based in Bengaluru. We help businesses run AI entirely on their own infrastructure: self-hosted LLMs, secure enterprise RAG, fine-tuned models, and AI agents that never send data outside the network. We serve clients across the US, UK, and EU, and our work spans the full private AI stack, from GPU infrastructure to production agents.

About the Role

We are hiring interns who are strong in any one of these four areas. You do not need all four. Pick your strongest layer and apply.

• LLMOps: serving open-weight models with vLLM or SGLang, GPU infrastructure, quantization, Kubernetes deployment, latency and cost benchmarking
• Enterprise RAG: ingestion and chunking pipelines, embeddings, hybrid retrieval and reranking, retrieval quality evals
• Model fine-tuning: dataset curation, LoRA/QLoRA and full fine-tunes, instruction tuning, eval design
• AI agents & workflows: multi-step agents, tool use, orchestration, memory, guardrails, workflow automation

Requirements

What You'll Do

• Build and ship working systems, not slide decks
• Own your work end to end: design, build, benchmark, document
• Work directly with the founders and senior engineers
• Go deep in your layer while getting exposure to the other three

What We're Looking For

• Proof of good work in your chosen area. That could be:
• A project you built and can demo
• Open source contributions
• Kaggle, GSoC, hackathons, or a solid technical write-up

Anything public and verifiable works. College and CGPA don't matter. What you've built does.

Beyond that: you read documentation, pick up new tools fast, and figure things out without waiting to be told.