Our new developers were able to hit the ground running, we've worked with them for over two years now, and they are truly part of our team.
Alison WhittleProduct Delivery Manager, BladeFSIn-house feel, nearshore
LlamaIndex Developers
British firms sit on decades of contracts, policies and reports, and RAG is how that archive becomes something staff can actually ask questions of. We embed LlamaIndex developers who have built retrieval systems in production, full time and on your hours.
- Production RAG experience, not tutorial projects
- Employed by us, embedded in your team
- On British hours for real-time collaboration
Index CreationRetriever PipelinesQuery OptimizationMonitoring & Analytics
Our Service
From your data to a dependable answer
Your engineer designs loaders, indexes and query pipelines around the shape of your data, not a demo dataset. We handle sourcing and employment; you manage the work. Matched candidates arrive within seven working days, for one monthly fee on a rolling monthly contract with 30 days notice.
- Pipelines designed around your actual document shapes
- Interviewing matched candidates within 7 working days
- Rolling monthly engagement, 30 days notice
Engineers you manage, employed by us
The full retrieval stack
- Build loaders and splitters for PDFs, HTML, Notion, and more.
- Index CreationDesign and implement dense or keyword-based indexes that scale.
- Retriever PipelinesChain together query engines, rerankers, and metadata filters.
- Query OptimizationImprove relevance, speed, and cost-efficiency of answers.
- Multi-Model CompatibilityPlug into OpenAI, Cohere, Claude, or fine-tuned models.
- Monitoring & AnalyticsTrack RAG pipeline performance and user search behavior.
The alternative
Get speed, fit and in-house feel without the hiring grind.
Cloud EmployeeIn-house hiringDev agenciesFreelancers
Speed to hire✓-✓✓
Flexibility to scale✓-✓✓
Developer fit (embedded)✓✓✓-
Full-time, only for you✓✓--
No overhead or upfront fees✓--✓
Solid lime = yes · outline lime = partial · grey dash = no
Vetting
You see two people - not 200 CVs.
Engineers vet engineers
A senior engineer runs a live technical conversation on the candidate's real stack, not a recruiter working from a keyword list.
Live coding, not take-homes
Real problems solved in front of an assessor, with anti-cheating checks. You see how they actually work, not what they submitted overnight.
A full profile, not a CV
Every candidate arrives with a CV, interview summary, coding-test breakdown and rate in pounds. You decide on evidence.
Every tab is a stage a candidate has to clear. Six of them, all run by our own internal engineers at Cloud Employee, before you see a name.
- Overview
- CV
- Tech interview
- Coding test
- Psychometric
- Soft skills
Scored by people. We use AI to cross-check our own consistency - never to decide who reaches your shortlist.
✓Luka M.
VettedSenior AI Engineer · Python · LLM systems · RAG · 6 yrs · Zagreb, Croatia (GMT+1)
Assessment
Six years in production Python, the last three on LLM systems - retrieval pipelines, eval suites, and agent tooling for UK fintech. Owns delivery end to end.
Stack
Python · LangGraph
English
C1 fluent
Overlap
8 hrs UK
Notice
2 weeks
AI in practiceShips with Copilot and Claude Code daily, and rewrote 40% of the generated code in his observed task - the judgement is his, the tooling only makes him faster.
Career history
2023 - now
Senior AI Engineer
UK payments platform · 40-person product team
Built the retrieval assistant now resolving 30% of tier-1 tickets; owns its eval suite and guardrails.
2020 - 2023
Backend Engineer, Python
Travel booking SaaS · Zagreb
Moved fraud scoring onto a real-time feature pipeline; cut false declines by 18%.
2019 - 2020
Data Engineer
Agency · Python, Postgres, AWS
- Python
- FastAPI
- LangGraph
- pgvector
- Evals & tracing
- AWS
- Docker
Technical interview
Assessed by Marco R., Principal Engineer
12 Jun 2026
55 min · live call
"Walked me through an assistant that was quietly hallucinating refund policy, how he caught it in evals, and what he got wrong on the first fix. Hire-ready for a senior seat."
Live coding test
Repair a leaking retrieval pipeline
88
score
Tests passed
21 / 21
Time used
62 of 90 min
Anti-cheat flags
0
retrieval.py · submitted diff
- hits = index.query(q, k=50)+ hits = index.query(rewrite(q), k=50, filter=tenant)+ hits = rerank(hits, q)[:8] # recall 0.62 -> 0.91+ assert_context_budget(hits, max_tokens=6000)
Psychometric · technical thinking
How he reasons under a real deadline - not a personality quiz.
Top 9%of engineers
we test
A 45-minute reasoning test, scored against the 4,000+ engineers we have already placed. Our assessors do the marking - AI only flags where our own scoring looks inconsistent.
Soft skills · working with your team
Spoken English
C1 · assessed on call
References
2 of 2 verified
"He raised the payment edge case nobody else had spotted, in writing, two days before release."
This is what you receive - not a CV.
Ask our AI anythingWhy Cloud Employee?
Retrieval quality is a judgement problem
A RAG system that retrieves the wrong passage looks confident and is worse than useless, so we vet for the evaluation habits that catch it. Vetting is CTO-led with live pair programming, we test how candidates use AI tooling in their own work, and the two-week money-back guarantee plus free replacement means the risk sits with us.
- CTO-led vetting with live pair programming
- Tested on how they evaluate retrieval quality, not just build it
- Two-week money-back guarantee plus free replacement
The operation behind the engineer
Payroll, HR and retention run by us, with a UK-based client success manager as your contact.
Fully supported
We handle the rest so your engineers can focus on building.
Performance reviews
Payroll & complianceEquipment
WorkspaceIn-house, without the friction
No upfront fees. No lock-in contracts.
- No placement or upfront fees
- Rolling 30-day contract, cancel anytime
- One monthly rate, everything included
Ready to find your engineer?
Tell us exactly who you need.
In 90 seconds
Two matched engineers in 7 days. No fees, no obligation.
What role are you hiring for?
Pick one to start - you'll see matching engineers at the end.
- Founded in 2014
- 97% stay 2+ years
- Replace if it isn't working
Got questions?
The questions CTOs and founders ask.
01How much does it cost to hire a LlamaIndex developer in the UK?
For most roles, 50 to 75% less than the full cost of a comparable British hire, including salary, employer national insurance, pension, recruitment fees and overheads. Yes, we place UK-based LlamaIndex engineers. Most of our clients still end up in Eastern Europe, the Philippines or Latin America, because the talent is comparable and the price is not, and Eastern Europe overlaps a British day almost completely. LlamaIndex and retrieval-augmented generation are so new that Britain has only a tiny pool of proven practitioners, which keeps local pay for them high.
02What is LlamaIndex and why do teams use it?
LlamaIndex is an open-source framework for connecting large language models to your own data, built around retrieval-augmented generation, or RAG. Teams use it because an LLM out of the box knows nothing about their contracts, tickets, policies or product docs, and LlamaIndex provides the machinery to change that, ingestion connectors, indexing strategies, query engines and agents that reason over private data. Its centre of gravity is data, distinguishing it from general orchestration frameworks. The trade-offs echo the wider ecosystem, fast-moving interfaces that can hide what a simpler pipeline would show. Use it when your feature depends on fresh, findable data.
03What skills should I look for in a LlamaIndex developer now?
Retrieval judgement is the skill that matters, because in RAG systems the model is rarely the problem, the context you feed it is. Look for engineers who reason about chunking, embedding choice, hybrid and reranked search, and metadata design, and who can say why a given corpus needs a given strategy. Evaluation is the twin skill, building sets that measure whether retrieval found the right passages. Data plumbing sits underneath, parsing messy documents and keeping indexes fresh, unglamorous work deciding whether the system survives contact with reality. Assistants write boilerplate, so the paid-for skill is diagnosing wrong answers.
04How do I assess a LlamaIndex developer, and what should I ask?
Assess a LlamaIndex developer with a retrieval post-mortem, give them a RAG system answering wrongly and ask them to find out why. Strong candidates work the pipeline in order, what was ingested, how it was chunked, what the query retrieved, what the model was actually shown, rather than jumping to prompt fixes. Ask how they would build an evaluation set and know the system improved. Probe data reality too, since production RAG is mostly wrestling PDFs and permissions. Watch whether they verify AI-generated retrieval code against known queries. Prefer diagnostic thinkers over reciters.
05Are LlamaIndex developers in demand, and is it worth building on?
Demand is strong and growing, because RAG has settled in as the default way companies make LLMs useful on private data, and LlamaIndex sits squarely in that lane. Almost every serious enterprise AI feature needs retrieval, long context windows have not killed it, and someone has to build and maintain those pipelines. Treat LlamaIndex fluency as the current expression of a durable skill. It is worth building on when your data is your moat and generic answers embarrass you. If your feature works fine on public knowledge, a simpler system is cheaper and easier to trust.
06Do your developers use AI tools, and how do you know the code is sound?
Yes, and in RAG engineering the deeper soundness question is not only the code, it is whether the system retrieves truth, so we test both. Generated pipeline code gets the standard treatment we vet for, read, tested, explained, never pasted blind. System soundness gets evaluation, query sets with known answers, and monitoring for the quiet decay that comes as documents change. Candidates are assessed live on these habits, pairing with a senior engineer who watches how they verify assistant output. Our own AI use follows the same rule, screening is augmented, hiring decisions are human.
07How does Cloud Employee vet LlamaIndex developers?
LlamaIndex developers pass our CTO-led vetting, the same four stages every Cloud Employee engineer faces, pointed at data and retrieval problems. There is a technical assessment, a live pair programming session with a senior engineer, a cultural fit screen and a psychometric assessment we built ourselves for software engineers. In pairing we set retrieval scenarios rather than toy algorithms, because that is where genuine production experience shows. AI supports our screening, a human makes every call. Interviews land inside 7 working days, and 97% of engineers stay beyond two years.
08How quickly can a developer start, and how does the engagement work?
You are typically interviewing matched candidates within 7 working days of a requirements call, and developers are often embedded and pushing code within about two weeks. From there it is a rolling monthly contract with 30 days' notice, one monthly fee, and no placement charges. You can scale up or down as the work changes, and you pay nothing to interview.
09What happens if the developer is not the right fit?
There is a two-week money-back guarantee, and if you want to continue we replace the developer free of charge. In practice this rarely comes up, because you interview a shortlist of two candidates who have already passed a CTO-led technical assessment and a live pair programming session, so the fit question is largely settled before anyone starts.
Proof, not promises
Hear from our customers
In their words
What the difference feels like
Alison WhittleProduct Delivery Manager, BladeFSWhat I love about Cloud Employee is that you have taken all of that hard work off my shoulders.
Marcus KilgourCTO, Salmon SoftwareWorking with Cloud Employee developers is great, because they're not afraid to push back. They're proactive, they're positive, and they feel like part of the team.
Doran EskinaziHead of Engineering, HealthpointeWe actually hired the whole team remotely, having never met them. And we made a bunch of really good hires.
Euan CameronCEO, WilloCloud Employee provides a level of professionalism, communication and support we haven't found elsewhere.
Trevor SathorManaging Director, Square EyeWorking in tandem with Cloud Employee we have successfully released a major version of our main software product during a critical period for us.
James StringerManaging Director, CleanLink