Generative AI Engineer Intern

Job Role:

Company:

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Stipend:

Duration: 6 Months

???? About Growhut

At Growhut

Generative AI Engineer Interns

???? The Role: Generative AI Engineer Agentic AI (Internship)

As an intern at Growhut, youll work at the cutting edge of agentic workflows

???? What Youll Do

• Design, build, and test

  agentic AI workflows

  using frameworks like

  Krivya, LangGraph, CrewAI, AutoGen

  , or

  Autogen Studio

  .
• Integrate LLMs (GPT-4, Claude, Lamma, etc.) into real-world automation pipelines with live APIs and tool usage.
• Deploy autonomous agents that can perform tasks such as research, document generation, summarization, and coordination.
• Work with

  retrieval-augmented generation (RAG)

  techniques, memory systems, and context-aware task planning.
• Experiment with prompt chaining, long-term memory, and multi-agent collaboration protocols.
• Contribute to building scalable backend infrastructure for inference, tool integration, and async workflows.
• Collaborate on internal research initiatives and proof-of-concept projects in AI-human collaboration.

???? Technical Requirements

Were looking for someone with hands-on experience or a firm grasp of the following:

Must-Have:

• Strong understanding of

  Agentic AI

  , multi-agent workflows, and orchestration strategies.
• Experience with

  open-source frameworks

  like

  LangGraph, Krivya, AutoGen, CrewAI

  , or similar tools.
• Familiarity with

  vector databases

  (e.g., Pinecone, Weaviate, Qdrant) and

  RAG systems

  .
• Proficiency in

  Python

  , and working knowledge of

  LangChain

  ,

  Transformers

  , and

  Prompt Engineering

  .
• Exposure to

  LLMs

  (e.g., GPT-4, Claude, Gemini, Mistral) and their APIs.
• Comfort with

  cloud-managed services

  : AWS Bedrock, Google Vertex AI, or Azure OpenAI.
• Understanding of

  tool calling

  ,

  function calling

  , and

  memory management

  in LLM contexts.
• Familiarity with

  LiveKit

  , real-time communication protocols, and event-driven systems.

Nice-to-Have:

• Experience with

  audio/voice models

  or

  multi-modal agents

  .
• There is interest in

  task decomposition strategies

  like ReAct, Tree of Thought, and Plan-and-Execute.
• Exposure to

  LangChain Expression Language (LCEL)

  and custom agent toolkits.

???? Why Join Growhut

• Build Real Systems

  : Not just research youll build end-to-end agentic products for real users.

• Mentorship from Experts

  : Collaborate with a team thats pushing boundaries in AI and automation.

• Global Exposure

  : We work with clients and users around the world across BFSI, health, SaaS, and beyond.

• Cutting-Edge Infrastructure

  : Work on high-impact projects using the latest open-source tools and enterprise-grade services.

???? The Growhut Difference

At Growhut, we believe in building executional AI

?? Ready to Apply

If youre serious about building the next generation of autonomous AI agents