Job Overview
Role: AI Engineer Intern Location: Bengaluru, Karnataka Experience: 0–1 Year Key Skills: LLMOps, Enterprise RAG, Model Fine-Tuning, AI Agents & Workflows, Private AI infrastructure
Job Description
Abstrabit Technologies Pvt Ltd is hiring for the position of AI Engineer Intern in Bengaluru. The company focuses on private AI infrastructure, including self-hosted LLMs, secure enterprise RAG, fine-tuned models, AI agents, and GPU infrastructure. This internship is designed for candidates who already have practical experience in at least one of four technical areas: LLMOps, Enterprise RAG, Model Fine-Tuning, or AI Agents & Workflows. Abstrabit places strong emphasis on demonstrable work, with projects, open-source contributions, or hackathons serving as evidence of capability.
Roles and Responsibilities
- Choose Your Strongest AI Layer: Identify and demonstrate meaningful work in one of four key areas: LLMOps, Enterprise RAG, Model Fine-Tuning, or AI Agents & Workflows.
- LLMOps: Work on serving open-weight models using vLLM or SGLang, GPU infrastructure, model quantization, Kubernetes deployment, latency benchmarking, and cost benchmarking.
- Enterprise RAG: Focus on ingestion pipelines, chunking strategies, embeddings, hybrid retrieval, reranking, and retrieval-quality evaluation.
- Model Fine-Tuning: Engage with dataset curation, LoRA, QLoRA, full fine-tuning, instruction tuning, and evaluation design.
- AI Agents and Workflows: Develop multi-step agents, tool use, agent orchestration, memory, guardrails, and workflow automation.
- Build and Ship Working Systems: Create demonstrative projects that include a working implementation, clear setup instructions, source code, reproducible environment, documentation, architecture information, and performance/evaluation results.
- End-to-End Ownership: Own work from design through delivery (Design → Build → Benchmark → Document), making technical decisions, implementing them, measuring results, and communicating findings.
- Working Directly With Senior Engineers: Collaborate closely with founders and senior engineers, discussing technical decisions, asking useful questions, defending design choices, and adapting approaches based on evidence.
Skills and Eligibility Criteria
Experience: 0–1 year.
Mandatory Technical Skills:
- Strong practical ability in at least one of the four AI areas (LLMOps, Enterprise RAG, Model Fine-Tuning, or AI Agents & Workflows).
Competencies:
- Relevant practical proof of work (working project, open-source contributions, Kaggle work, GSoC, hackathons, or strong technical write-up).
- Ability to read technical documentation and learn new tools quickly.
- Ability to investigate problems independently and work without waiting for step-by-step instructions.
- Strong communication and initiative.
- Documentation and learning ability.