Artificial Intelligence Intern

About the role

We are looking for someone who has moved past "I use ChatGPT" and into "I build things with LLMs."

At Nexus Growth Advisors, AI is not a side experiment — it is becoming part of what we deliver. You will work on two fronts. Internally, you will automate the repetitive work that eats our teams' days: research, documentation, reporting, data extraction, follow-ups. Externally, you will help design and build AI solutions for our clients — custom agents, document-processing pipelines, internal copilots, workflow automation — and sit in the room while we scope them.

That second half is what makes this role different from most AI internships. You will talk to clients. You will hear a vague business problem, translate it into something an LLM can actually do reliably, and then build it. You will also be the person who says "this is not a good use of AI" when that is the honest answer.

We are hiring for capability, not credentials. If you have built a working agent — even a scrappy one — and can walk us through why you made the architectural choices you did, your degree does not matter to us.

What you'll do

Building

• Design and build custom AI agents — tool-calling, multi-step workflows, agents that take real actions in real systems
• Build RAG pipelines over document sets: chunking, embeddings, vector stores, retrieval quality, evaluation
• Write prompts as engineering artifacts — versioned, tested, with clear failure modes documented
• Integrate LLM APIs (OpenAI, Anthropic, Google, open-weight models) into working applications
• Connect AI systems to the tools a business actually runs on, via APIs, webhooks and MCP servers
• Build automations using no-code / low-code platforms (n8n, Make, Zapier, Power Automate, Apps Script) where that's the faster answer
• Build dashboards and internal tools so people can see and use what you've built

Client-facing

• Join client discovery calls, understand the business problem underneath the request, and shape it into a scoped AI solution
• Build demos and proofs of concept fast enough to be useful in a sales conversation
• Deploy solutions at client sites, train their teams, and support them after go-live
• Write documentation and SOPs a non-technical client can actually follow

Judgement

• Evaluate and stress-test AI outputs before anything reaches a client — accuracy, hallucination, edge cases
• Track what's genuinely new in the LLM and agent space and give us a straight read on what's worth adopting
• Handle client data with strict confidentiality; understand where data goes when you call an API

What we're looking for

Must have

• Hands-on experience building with LLMs beyond chat — API calls, prompt engineering, structured outputs
• Working understanding of how agents function: tool use, function calling, memory, planning loops, why they fail
• Understanding of RAG — embeddings, vector databases, retrieval, and why retrieval quality is usually the bottleneck
• Python (or JavaScript) at a level where you can build and debug a working application
• Comfort with APIs, JSON, and reading technical documentation without hand-holding
• Clear spoken and written English — you will be in front of clients
• Ability to explain a technical decision to someone with no technical background
• Willingness to work in-office in Delhi

Strongly preferred

• Any agent or LLM framework: LangChain, LangGraph, CrewAI, LlamaIndex, Claude Agent SDK, OpenAI Agents SDK, or your own from scratch
• Vector databases: Pinecone, Weaviate, Qdrant, Chroma, pgvector
• Familiarity with MCP (Model Context Protocol) or similar tool-integration standards
• Experience evaluating LLM output systematically rather than by vibes
• Any exposure to finance, accounting, tax, consulting or business operations
• Deployment experience — getting something off your laptop and into someone else's hands

Pay: ₹10,000.00 - ₹25,000.00 per month

Benefits

• Paid sick time
• Paid time off

Work Location: In person