AI Engineering Intern

Tapza Technologies

Hyderabad

On-site

INR 167,000 - 279,000

Full time

2 days ago
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Job summary

Tapza Technologies in Hyderabad, Telangana, is offering an AI Engineer Intern position in a Healthcare Tech setting. The role involves hands-on work with LLMs, LangGraph, RAG, and Open-Source AI models to build prototypes and move successful experiments toward production.

You will write clean Python code, explore real-world AI pipelines, and contribute to healthcare AI applications across pharmacy and clinical workflows. Freshers and experienced candidates encouraged to apply.

Qualifications

  • Strong Python programming skills.
  • Solid fundamentals in ML/DL.
  • Interest in LLMs and Generative AI.
  • Familiarity with RAG, embeddings and vector search.
  • Experience with LangGraph/LangChain or similar AI frameworks.
  • REST APIs and software engineering basics.
  • Strong debugging and problem-solving skills.
  • Willingness to learn new AI technologies.

Responsibilities

  • Build LLM-powered applications and AI agents for healthcare use cases.
  • Design agentic workflows using LangGraph and related frameworks.
  • Develop RAG systems with embeddings and vector databases.
  • Experiment with open-source LLMs like Llama, Qwen, Mistral, Gemma.
  • Develop conversational AI with STT and TTS.

Skills

Python
Machine Learning
LLMs
Generative AI
RAG
LangGraph
LangChain
REST APIs
Problem-Solving
Learning Quickly

Tools

LangGraph
LangChain
Vector Databases
PyTorch
Open-Source LLMs

Job description

AI Engineering Intern
  • ₹15,000 – ₹25,000 per month • No equity
  • Hyderabad
  • No experience required
  • Internship
About the job

AI Engineer Intern

Company: Tapza Technologies

Industry: Healthcare Technology

Location: Hyderabad, Telangana

Work Mode: On-Site

Employment Type: Full-Time Internship

Stipend: ₹15,000 – ₹25,000 per month

Experience: Freshers / Experienced Candidates

About Tapza Technologies

Tapza Technologies is a healthcare technology company building AI-powered software solutions for pharmacies, healthcare providers, and the broader healthcare ecosystem.

We are looking for an enthusiastic and technically strong AI Engineer Intern to join our engineering team and work on real-world AI applications involving LLMs, Generative AI, AI Agents, RAG, Voice AI, OCR, and Open-Source AI Models.

This is a hands-on engineering role where you will experiment with emerging AI technologies, build prototypes, solve real-world healthcare problems, and contribute to taking successful AI solutions toward production.

Key Responsibilities

  • Build LLM-powered applications and AI agents for real-world healthcare use cases.
  • Design and develop agentic workflows using LangGraph and related frameworks.
  • Build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, retrieval, and reranking.
  • Experiment with and integrate open-source LLMs such as Llama, Qwen, Mistral, Gemma, and other emerging models.
  • Develop conversational AI applications integrating Speech-to-Text (STT), LLMs, and Text-to-Speech (TTS).
  • Work on AI-powered solutions for pharmacy and healthcare workflows.
  • Build and optimize real-time AI systems with a focus on responsiveness, reliability, and scalability.
  • Work on Real-Time AI and Low-Latency Systems, optimizing end-to-end AI pipelines.
  • Explore streaming, asynchronous processing, caching, parallel execution, and efficient model inference.
  • Integrate AI systems with APIs, databases, vector databases, and external healthcare tools.
  • Experiment with different models, prompts, retrieval strategies, and agent architectures.
  • Evaluate AI systems based on accuracy, latency, relevance, reliability, and hallucination.
  • Build prototypes and contribute to converting successful AI experiments into production-ready solutions.
  • Write clean, modular, maintainable, and well-tested Python code.
  • Stay updated with the latest developments in Generative AI, Agentic AI, open-source models, and AI engineering.

Required Skills

  • Strong programming skills in Python.
  • Good understanding of Machine Learning and Deep Learning fundamentals.
  • Strong understanding or practical interest in LLMs and Generative AI.
  • Familiarity with RAG, embeddings, and vector search.
  • Familiarity with LangChain, LangGraph, or similar AI frameworks.
  • Understanding of REST APIs and software engineering fundamentals.
  • Strong problem-solving and debugging skills.
  • Ability to learn new AI technologies and frameworks quickly.
  • Strong interest in building practical AI applications.

Nice to Have

  • Hands-on experience with LangGraph and AI Agents.
  • Experience building RAG applications.
  • Experience with vector databases such as FAISS, Qdrant, Pinecone, Weaviate, or Milvus.
  • Experience with Hugging Face Transformers.
  • Experience working with Llama, Qwen, Mistral, Gemma, or other open-source LLMs.
  • Exposure to STT/TTS and Voice AI systems.
  • Experience with Whisper or other speech models.
  • Familiarity with PyTorch.
  • Exposure to vLLM, Ollama, or other LLM inference frameworks.
  • Understanding of Real-Time AI and Low-Latency Systems.
  • Experience with Git, Docker, or cloud platforms.
  • Experience with AI/ML personal projects, GitHub contributions, hackathons, research, or open-source projects.
  • Exposure to OCR, document intelligence, medical data, pharmacy systems, or healthcare applications is an added advantage.
  • Real-Time AI & Low-Latency Systems

You may work on real-time AI pipelines such as:

  • User Input → STT → AI Agent / LangGraph → RAG / Tools → LLM → TTS → Real-Time Response

You will explore ways to make these systems faster, more reliable, and production-ready through: Streaming inference; Asynchronous processing; Parallel execution; Caching; Efficient retrieval; Model and inference optimization; Reducing unnecessary LLM calls; Identifying and resolving pipeline bottlenecks; Improving end-to-end response latency

Healthcare AI Applications

  • Pharmacy management
  • Medicine and product intelligence
  • Prescription and medical document processing
  • AI-powered OCR and document extraction
  • Healthcare data processing
  • Intelligent search and retrieval
  • Pharmacy inventory intelligence
  • Conversational AI for healthcare workflows
  • Automated reports and insights
  • AI-powered healthcare assistants
  • Voice-enabled healthcare applications

Who Should Apply?

We are looking for freshers and experienced candidates who are passionate about AI and enjoy building real-world applications.

You do not need to know every technology listed above. We value candidates who demonstrate:

  • Strong Python and programming fundamentals
  • Practical understanding of AI/ML concepts
  • Curiosity about Generative AI and emerging technologies
  • Hands-on project experience
  • Strong problem-solving and debugging skills
  • Ability to learn quickly
  • A strong builder mindset
  • Willingness to experiment, test, and iterate
  • Candidates with personal projects involving LLMs, RAG, AI Agents, Voice AI, OCR, or open-source models will be highly valued.

Educational Background

Candidates with a degree or relevant technical background in:

  • Computer Science
  • Artificial Intelligence
  • Data Science
  • Information Technology
  • Electronics / Electrical Engineering
  • Or a related technical field
  • Freshers with strong practical AI/ML projects are encouraged to apply.

Core Technologies

Python • LLMs • LangGraph • RAG • AI Agents • Open-Source LLMs • STT • TTS • OCR • Vector Databases • APIs • Real-Time AI • Low-Latency Systems • PyTorch

What You Will Get

  • Hands-on experience building real-world AI applications for healthcare.
  • Exposure to modern Generative AI and Agentic AI technologies.
  • Opportunity to work with LLMs, RAG, AI Agents, Voice AI, OCR, and real-time AI systems.
  • Practical experience in AI prototyping and production engineering.
  • Opportunity to work on AI products used in the pharmacy and healthcare ecosystem.
  • Exposure to real-world healthcare data and workflows.
  • Mentorship and experience working in a product-focused technology environment.
  • Potential opportunity for a full-time position based on performance and business requirements.
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