Skip to main content
RAG Developers

Hire Dedicated RAG Developers

Add a vetted RAG developer to build retrieval pipelines that ground AI answers in your own documents and data, with sources cited on every answer.

50+ ERP and software projects. Zero failed projects since 2021.

Retrieval Pipeline
🔍
Query
›
📊
Vector search
›
📄
Retrieved chunks
›
💬
Answer
1-2 wk
Typical shortlist time
100%
Screened on real retrieval builds
Flexible
Full time, part time or project
Free
Replacement if not a fit
Why It Matters

A general answer is not the same as a grounded one

Without retrieval, an AI answer is a general guess. With it, the answer is tied to your actual documents, and you can check where it came from.

Grounded in Your Content

Answers tied to what you actually have on file

Policy documents, product manuals, contracts and internal wikis all change constantly. A dedicated RAG developer builds the pipeline that indexes this content and retrieves the right piece at the moment someone asks.

  • Documents chunked and indexed correctly.
  • The most relevant pieces retrieved per query.
  • Answers grounded in your actual content.
A developer building a retrieval pipeline
Sources You Can Check

Every answer traces back to a source

A grounded answer is only useful if you can verify it. A dedicated developer builds citations into the pipeline so every answer points back to the document or section it came from.

  • Source citations on every generated answer.
  • Easy verification instead of blind trust.
  • Indexes kept current as documents change.
A remote developer in a video call with a client team
What the Pipeline Looks Like

The same four stages, whatever the document set

Policies, manuals or contracts all move through this same retrieval shape.

Example: An Internal Policy Assistant
💬
Employee question
›
📊
Policy search
›
📄
Matching clause
›
✅
Cited answer
How Hiring Works

From requirements to a working developer in about two weeks

1
Share requirements
Tell us the documents or data you want searchable and the questions people will ask.
2
Shortlist
We match developers by retrieval pipeline experience and send you 2 to 3 profiles within days.
3
Interview
You interview the shortlist directly and pick the developer who fits your content and team.
4
Onboard
The developer reviews your document set and starts building the indexing pipeline in the first week.
5
Scale as needed
Add more document sources or a second developer as usage grows.
What's Included

Everything you need to run the engagement smoothly

🎯

Dedicated to your project

The developer works only on your account, not split across other clients' pipelines.

💬

Direct communication

You talk to the developer directly on your tools, with no account manager relay in between.

📅

Flexible contracts

Full time, part time, or a fixed scope of work. Scale up or down with notice, not a long lock-in.

✅

Citation accuracy checks

Answers spot-checked against their cited sources before the pipeline goes live.

🌐

Timezone overlap

Working hours arranged to overlap with your team for stand-ups and reviews.

🔐

Replacement guarantee

If the developer is not the right fit, we replace them at no extra cost during the engagement.

What Changes

What a dedicated RAG developer changes for your knowledge base

Grounded
Answers tied to your documents
Cited
Sources on every answer
Current
Indexes as documents change
Fewer
Wrong or made-up answers
Model-agnostic
Approach fit to your data
Lower
Cost than a full-time direct hire
Why Us

Why teams hire RAG developers through TCB Infotech

1
We build retrieval into real systems
We ground AI answers in ERP and business documents ourselves, so our developers are tested on real content, not trivia.
2
Fast, honest shortlisting
You see 2 to 3 profiles, not a stack of resumes, and we tell you plainly if a fit is not right.
3
Direct access, no relay
You manage the developer's day to day work directly, on your tools and your process.
4
Pipelines you can keep
Indexing setup and retrieval logic are documented and handed over cleanly if the engagement ends.
5
No long lock-in
Scale the engagement up or down with notice, based on your actual retrieval roadmap.
6
Proven delivery
50+ ERP and software projects, with zero failed projects since 2021.
FAQ

Hiring RAG developers, answered

What does a dedicated RAG developer do?
They build the retrieval pipeline behind an AI answer: chunking and indexing your documents, searching for the most relevant pieces at query time, and grounding the generated answer in what was actually retrieved, with sources cited.
How is RAG different from just asking a model a question?
Asking a model directly relies on what it already knows in general. RAG retrieves the specific, current information from your own documents first, so the answer is grounded in your actual content rather than a general guess.
Can we see where an answer came from?
Yes. A properly built RAG pipeline cites the source document or section behind each answer, so you can verify it rather than take it on faith.
How is this different from an AI agent developer?
A RAG developer focuses on retrieval and grounding a single answer in your documents. An agent developer builds a multi-step reasoning and tool-use loop that can take actions, not just answer questions. The two are often combined; ask us and we will scope your use case.
What is the engagement model?
You can hire full time, part time, or for a fixed project. Contracts scale up or down as your retrieval roadmap changes, with no long lock-in period.
What if the developer is not the right fit?
We replace the developer at no extra cost during the engagement, and hand over the retrieval pipeline and indexing setup to the new developer.

Hire a Dedicated RAG Developer

Book a free consultation. Tell us what content you want searchable, and we will shortlist developers who fit your data and your team.

Book a Free Consultation →

No commitment. See a shortlist before you decide.

RAG Developer Hiring Features

How Hiring a Dedicated RAG Developer Works

From the requirements call to a cited answer in production. Here is how we vet, match and onboard every RAG developer we place.

Core Process

Vetting, matching and onboarding, in that order

Vetting

Every developer is tested on real retrieval builds

Before a developer joins our bench, they are tested on chunking and indexing strategy, retrieval quality, and a hands-on task building a pipeline that answers questions from a real document set with citations.

  • Chunking and indexing strategy.
  • Retrieval quality tuning.
  • A real cited-answer build task.
A technical interview and retrieval pipeline assessment
Matching

You get a shortlist, not a resume pile

We match developers to your specific content: the document types you have, the scale of your knowledge base, and the timezone overlap that works for your team. You see 2 to 3 fitting profiles, not fifty.

  • Matched to your document types.
  • Matched to the scale of your content.
  • Matched to your working hours.
Reviewing a shortlist of developer profiles
Onboarding and Management

A structured start, then you take the lead

The developer reviews your document set, agrees the chunking and citation approach with you, and starts building the indexing pipeline in the first week. You manage priorities directly from there.

  • A review of your document set.
  • An agreed citation and grounding approach.
  • Direct day-to-day management by your team.
A developer onboarding onto a new retrieval project
What You Get

Everything included in the engagement

🎯

Dedicated developer

Works only on your account, not shared across other clients' pipelines.

💬

Direct communication

Access to the developer on your own tools, with no account manager relay.

📅

Flexible contracts

Full time, part time, or a fixed scope, adjustable with notice as your roadmap changes.

✅

Citation accuracy checks

Answers spot-checked against their cited sources before launch.

🌐

Timezone overlap

Working hours arranged to overlap with your team for stand-ups and reviews.

🔐

Replacement guarantee

A new developer at no extra cost if the current one is not the right fit.