Hire AI experts
Hire AI experts for LLM, RAG, agent and MLOps work
Choose the AI role you need, not just a developer. Xcrino provides vetted in-house AI engineers for LLM applications, RAG systems, AI agents, forecasting and MLOps. You interview every candidate, and they work inside your process.
Shortlist within 72 hours, a 1-week trial and a one-month minimum engagement.
- LLM engineer
- RAG engineer
- AI agent engineer
- MLOps
- Forecasting
- Python
- 560
- Clients served
- 69+
- Developers
- 94%
- Project success rate
- 26
- Countries served
At a glance
Key takeaways
- Hire by role (LLM, RAG, AI agent, MLOps or forecasting) instead of asking for a generic AI developer.
- Start with one role, then add others as the project grows.
- Every AI role comes with a shortlist in 72 hours and a one-week trial.
- If you are unsure the idea will work, begin with a short AI proof of concept.
- You interview every candidate. Source code and IP transfer to you on full payment.
AI experts
What is the difference between an AI expert and an AI developer?
An AI expert is an engineer with depth in one part of applied AI, for example building LLM features, retrieval systems, agents or the pipelines that keep models running. A general AI developer covers many tasks. Hiring by role helps you pay for the exact skill your project needs.
This page helps you choose the role. For the full developer offer and engagement terms, see hire AI and machine learning developers.
Roles
Which AI roles can you hire?
Pick the role that matches your first deliverable.
- LLM
LLM Application Engineer
Builds chat, summarization and extraction features on top of large language models.
- Retrieval
RAG Engineer
Connects models to your documents and data through RAG, so answers come with sources.
RAG - Agents
AI Agent Engineer
Builds agents that complete tasks across your business systems, with permissions and human approval.
- Operations
MLOps Engineer
Deploys, monitors and retrains models so they stay accurate in production.
- Data
Forecasting and Data Scientist
Builds forecasting, scoring and recommendation models from your own data.
- Quality
AI Evaluation Engineer
Designs the tests that measure accuracy and safety before and after launch.
Choose
Which AI role should you hire first?
Start with the role that matches your first deliverable. If you are adding chat or summarization to a product, hire an LLM application engineer. If answers must come from your own documents, hire a RAG engineer. If work should run across your systems, hire an AI agent engineer. If models already exist but fail in production, hire an MLOps engineer.
Most projects need a second role by the second month, for example an evaluation engineer next to an LLM or RAG engineer. You can add roles month by month.
Role guide
When should you hire each AI role, and what should you ask?
| Role | Hire when | Ask in the interview |
|---|---|---|
| LLM application engineer | Hire when: You are adding generative features to a product. | Ask in the interview: How do you handle prompts, limits and failures in production? |
| RAG engineer | Hire when: Answers must come from your documents. | Ask in the interview: How do you split and retrieve documents, and check that an answer is grounded in the source? |
| AI agent engineer | Hire when: Work should run across your systems. | Ask in the interview: Which actions need human approval, and how do you limit permissions? |
| MLOps engineer | Hire when: Models exist but need deployment and monitoring. | Ask in the interview: How do you detect drift and roll back a model? |
| Forecasting or data scientist | Hire when: You need predictions from your own data. | Ask in the interview: How do you validate on data the model has not seen? |
| AI evaluation engineer | Hire when: You must prove accuracy and safety before launch. | Ask in the interview: How do you build a test set and catch regressions? |
Process
How does hiring an AI expert work?
From role brief to an engineer in your stand-up, usually within a week.
- 01
Name the role
Tell us the AI work ahead, the stack and the hours overlap you need.
- 02
Shortlist in 72 hours
We send vetted profiles that match the role.
- 03
You interview
You interview every candidate and choose.
- 04
Trial and continue
A one-week trial, then continue monthly or ask for a replacement.
Quality
How do we keep AI work reliable?
AI systems fail in ways ordinary software does not. Our experts build in these safeguards:
- Evaluation before launch: A test set of real examples measures accuracy and catches regressions before and after each release.
- Human approval for actions: Agents that act on your systems ask a person to approve important steps.
- Controlled data access: You agree in advance which data and which AI providers are used, and how it is isolated.
- Monitoring in production: Quality, drift and failures are watched after launch, with a way to roll back.
- Reviewed, documented work: Code is reviewed, and notes and the source repository are handed over to you.
Delivery
How do AI experts work inside your team?
- They join your process: Stand-ups, your board and your code review.
- Agreed hours overlap: Working hours are agreed to overlap with your time zone.
- A technical lead behind them: Someone senior to escalate to when you need it.
- Replacement with handover: If a developer is not the right fit, we replace them and hand over the work.
- Your confidentiality terms: An NDA whenever you ask, and all code and IP transfer to you on full payment.
Prepare
What should you prepare before hiring an AI expert?
- The outcome you want, for example fewer manual hours or faster answers
- The data the system will use, and who owns it
- How you will judge success, with a few real examples
- Rules about data access, such as an NDA or masked data
- The hours overlap you need with the developer
Next step
Should you hire an expert or prove the idea first?
If you already know what to build, hire the role. If you are not sure the idea will work on your data, a fixed-scope proof of concept of 2 to 4 weeks gives a clear go or no-go decision before you commit to a monthly hire.
AI proof of conceptHire AI and machine learning developersAI agent development
Trust
Why trust Xcrino with your AI hiring?
- AI-first company: We build AI agents, RAG systems and forecasting models ourselves, so we know what to screen for.
- In-house employees: Every expert is an Xcrino employee, not a freelancer or subcontractor.
- You decide: You interview every candidate before anyone joins.
- Delivery record: 94% of projects delivered on time and on budget, across 560 clients in 26 countries.
- Real AI results: A demand-forecasting model for a Tokyo brand lifted online sales revenue by 20 to 35 percent year on year.
- Profiles you can check: Company profiles on Clutch and TopDevelopers to review independently.
Get a quote
Tell us which developer you need
Share the stack, seniority, hours of overlap and the first tasks. We send a shortlist within 72 hours, and you interview every candidate.
Reach us
New Delhi, India
FAQ
Hiring AI experts: questions answered
Roles, vetting and how we work with your team.
What is the difference between an AI expert and an AI developer?
An AI expert is an engineer with depth in one area, such as LLM features, retrieval, agents or MLOps. A general AI developer covers a wider range of tasks. Hiring by role lets you pay for the specific skill your project needs.
Which AI role should I hire first?
Start with the role that matches your first deliverable: an LLM application engineer for chat or summarization features, a RAG engineer when answers must come from your documents, an AI agent engineer for work across systems, or an MLOps engineer when models already exist but break in production.
Can one person cover RAG and AI agents?
On a small project, yes: one engineer can build retrieval and a simple agent. As scope grows, split the roles so each person goes deep.
How are your AI experts vetted and kept accountable?
They are Xcrino employees, not freelancers or subcontractors. You interview every candidate, a technical lead is available if you need to escalate, and if the fit is wrong we replace the developer with a handover.
How fast can I get a shortlist?
Within 72 hours of agreeing the role brief, you receive vetted profiles to interview.
Is there a trial period and a minimum contract?
Yes. There is a one-week trial and a one-month minimum engagement. If a developer is not the right fit, we replace them.
Should I hire an expert or start with a proof of concept?
If you know what to build, hire the role. If you are not sure the idea will work on your data, a fixed-scope proof of concept of 2 to 4 weeks gives a clear go or no-go decision before you commit to a monthly hire.
Will you sign an NDA, and who owns the work?
Yes. We sign an NDA whenever you ask, and all source code and intellectual property transfer to you on full payment.