Hire developers
Hire AI & LLM Developers
AI features that answer correctly, cost what you expected and fail gracefully when they do not.
MeetOnChai Studio places AI developers who build LLM features into real products: support assistants, document search, data extraction and agents that call your APIs. They treat it as software engineering, with evaluations, cost tracking and guardrails, not as a demo that falls over in week two. You interview them first and own every prompt, pipeline and line of code.
- Interview before you commitYou meet the developer and decide before any work starts.
- You own the codeWork happens in your repository from day one. Code, designs and accounts are yours.
- NDA before detailsWe sign your NDA, or ours, before you share anything sensitive.
- Your hours, not oursOverlap with India, the Gulf and Europe is easy from GMT+5:45, and we flex for US mornings.
Skills
What our ai & llm developers bring.
Core
- LLM APIs from Anthropic, OpenAI and Google
- Retrieval-augmented generation (RAG)
- Tool calling and structured outputs
- Agent workflows and orchestration
- Prompt design and versioning
- TypeScript and Python
Ecosystem
- Vercel AI SDK
- Model Context Protocol (MCP) servers
- Vector search with pgvector, Pinecone or Qdrant
- Embeddings and reranking
- Document parsing and chunking pipelines
- Open-weight models where privacy or cost requires
Practices
- Evaluation sets and regression testing for prompts
- Token cost tracking and caching
- Guardrails against prompt injection
- Streaming UX and graceful fallbacks
- Logging and tracing of model calls
On your project
What they'll own.
- 01Find the AI use cases in your product that are worth building and say plainly which ones are not
- 02Build RAG pipelines that answer from your own documents and cite their sources
- 03Connect models to your systems through tool calls so they can look things up and take actions safely
- 04Set up evaluations so you know when a prompt or model change makes answers worse
- 05Keep token costs and latency in check with caching, smaller models and sensible limits
- 06Ship features behind flags, monitor real usage and demo results every week
Right role?
When this is the hire you need.
- 01
Adding AI to a product you already have
Support assistants, smart search, summarization and extraction bolted onto an existing app. An AI developer integrates with your stack instead of rebuilding it.
- 02
Automating document-heavy work
Invoices, contracts, forms and support tickets that people read and retype. LLMs with structured outputs handle a lot of this reliably when built with checks.
- 03
Not a replacement for an ML research team
Training models from scratch or novel research needs ML specialists. Our AI developers build on top of existing models, which covers what most products need.
How hiring works
From chai call to first commit.
- Step 1
Chai call
We talk about your product, stack, team and what the developer needs to own.
- Step 2
Profiles
You see matched profiles with relevant work, not a stack of CVs.
- Step 3
Interview
You interview the developer and decide. Nothing starts until you're sure.
- Step 4
Start
NDA signed, access set up, work happens in your repo. Weekly demos from then on.
Engagement models
Hire one developer, a pod, or a project.
Pick the one that matches how certain you are about scope. We'll recommend one on the first call, and you can switch later.
Well-defined MVPs, stores and websites
Fixed-scope project
We agree the scope, the price and the milestones up front. You pay per milestone, and scope changes are quoted before they happen, never after.
- Fixed price per milestone
- Written scope with what's in and out
- Best when you know what v1 is
Ongoing products and growing startups
Dedicated developer or team
One developer or a small pod works on your product full time, inside your tools and rituals. You set priorities; we handle the people, reviews and quality.
- Monthly engagement
- Your backlog, your sprint rituals
- Scale up or down with notice
Evolving products and discovery work
Time & materials
You pay for the hours actually spent, tracked against a sprint budget. Good when the problem is still being shaped and flexibility matters more than a fixed number.
- Sprint budgets, not blank cheques
- Weekly time reports
- Change direction any sprint
Related technology
FAQ
Hiring ai & llm developers: questions.
Which model will you use, OpenAI, Claude or Gemini?
Whichever performs best on your evaluation set at a cost you can live with. We often keep the code provider-agnostic so you can switch when prices or quality change, which they do often.
Is our data safe if we send it to an LLM?
Major providers do not train on API data by default, and we use enterprise settings where needed. For sensitive data, we can redact before sending or run an open-weight model on infrastructure you control.
How do you stop the AI from making things up?
Ground answers in your own data with RAG, require citations, use structured outputs and test against real questions. Hallucinations do not drop to zero, so the product is designed to handle the ones that slip through.
Can an AI developer add a chatbot to our existing website or app?
Yes, and that is one of the most common requests. They connect it to your content and, where useful, your APIs, so it can answer real questions about orders, accounts or products.
How much will the AI part cost to run?
It depends on volume and model choice. Your developer will estimate token costs from real usage early, then cut them with caching and smaller models where quality allows. No surprises on the bill.
Every project starts with a conversation
Got an idea? Let's talk over chai.
A free 15-minute call. No pitch deck, no obligation. You leave with an honest read on what to build first.
- We reply within 24 hours, usually much sooner.
- NDA signed before you share the details.
- Based in Kathmandu, working with Nepal, India and worldwide.