Artificial Intelligence Engineer Intern
2 days ago
Company Description
InfraDock AI is an early-stage technology startup focused on bringing cutting-edge artificial intelligence to the construction industry.
Our team is developing a platform that will use advanced AI to understand, analyze, and extract insights from construction documents at scale. By streamlining document-heavy workflows and bringing critical insights to the surface, we enable construction teams to focus on execution and quality.
Role Overview:
We are looking to hire an
AI Engineer
for a
Full-Time Paid Internship
, and in a
Hybrid
role (with the office based in Delhi NCR, India). As part of the role, you will work directly on one of the core pipelines by:
- Designing custom domain-aware ingestion processes to interpret project text documents like a domain-expert
- Researching and implementing cutting-edge RAG techniques to enhance retrieval and reasoning systems
- Building a professional-grade Agentic Workflow to bring intelligence and insights from unstructured project documents directly to industry experts
This role is hands-on — you'll design, build, and optimize LLM pipelines, embedding models, and chunking logic to improve retrieval and reasoning quality across large, heterogeneous EPC documents.
You'll Be a Great Fit If You Have:
Prerequisites:
- B.Tech / M.Tech / B.Sc / M.Sc in CS, AI/ML, Data Science, or related fields
- Work or project experience in building smart RAG pipelines over unstructured data
- Hands-on with prompt engineering and fine-tuning AI agents
- Working knowledge of LangChain / LangGraph/ CrewAI and Agentic Workflows
Technical Skills Required:
- Python expert: NumPy, pandas, dataclasses, type hints
- Strong fundamentals in Natural Language Processing (NLP)
- Experience with and strong understanding of RAG architectures: Chunking strategies, metadata enrichment etc
- Hands-on with vector databases: FAISS / ChromaDB / Pinecone / Elasticsearch
- Project experience in using document parsing tools , PyMuPDF, PDFPlumber, OCR) for multi-format unstructured files
- Solid understanding of different embedding models (OpenAI/Instructor/MiniLM/Mistral embeddings)
- Solid understanding of information retrieval techniques: Similarity search, neighbor expansion, context-aware retrieval, contextual compression etc
- Experience with different Reranking methods and models like BGE/MS-Marco Cross-Encoder Rerankers
What You'll Build / Learn:
During the Internship:
- Understand and then build on the current RAG + LLM architecture
- Enhance and test chunking, embedding and retrieval logic
- Implement cross-encoder reranking and query decomposition models/agents
- Optimize retrieval scoring, clustering, and reasoning chains
- Work on end-to-end multi-agent workflows and integrate them with orchestration frameworks like LangGraph / LangChain / CrewAI etc
By the End of the Internship:
You'll have deep, hands-on experience in:
- Building production-grade RAG + multi-agent pipelines
- Designing domain-aware AI systems for multi-format document reasoning
- Working with LangGraph / LangChain
- Real-world application of LLM reasoning, retrieval, and orchestration
Soft Skills:
- Strong analytical and research-based mindset, with a drive to solve real-world industry level problems
- Enjoy taking on responsibilty, brainstorm ideas and experiment with new methods
- Strong interest in enhancing retrieval techniques,and constructing agentic workflows
- Comfortable reading research papers / articles and translating into code
Duration:
3-6 Months (with potential to convert to full-time)
Location
: Hybrid (Delhi NCR, India)
Why Join Us:
- Work on real AI systems, not toy projects
- Build cutting-edge AI solutions for industry-specific problems
- Build your portfolio with production-grade RAG and agentic workflows
- Potential to convert to full-time after internship
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