Parvessh Agarwal
Founder & CEO
An entrepreneur at heart. He links business analysis, strategy, clear goals and ROI to practical technology.
LinkedIn →Hire AI developers
with one contact from brief to delivery.
PixelCrayons is your point of contact for hiring an AI developer. We scope the role and write the proposal. Our sister company ValueCoders finds and supplies the AI engineer, or a team. They work under that one proposal and account team. You interview the actual builder and sign one contract. Want PixelCrayons to scope and build a defined AI feature project instead of a hire? See our AI services.
Interview before signing · One contact throughout
Tell us about the role
Start Your Enquiry
Send a short brief. Once we have a complete brief, we confirm the date you will receive your itemised proposal.
What you get
PixelCrayons is your point of contact for hiring an AI developer. Our sister company ValueCoders sources and delivers the engineer. You brief us once and interview the engineer before anything is signed. One PixelCrayons account team handles escalation, billing and status. For a scoped AI project instead of a hire, see our AI services.
- Vetted on AI features in live productsEvery engineer we propose has taken an AI feature live, vetted to ValueCoders' delivery standards.
- One point of contact for everythingPixelCrayons scopes the role and handles escalation, billing and status. A ValueCoders engineer builds the feature.
- Honest advice on the right routeYou hear early if the job needs another specialist or a scoped project from our AI team.
Our work
See what we've built
and the results it brought.
Real projects for real clients, with results we can show.
2004
Established
500+
Agencies served
4,500+
Projects delivered
340%
Revenue growth · 7 months
eCommerce
+127%
Organic traffic · 5 months
SaaS
85%
Faster delivery · backlog cleared
via agency partner
Where the work happens
What they cover
AI developer skills
for features that work in your live product.
Each engineer is vetted on real AI features in live products, not prototypes chasing the newest model. They come from ValueCoders' team and are matched to your gap.
Building AI features
- Connecting large language models (LLMs, the AI behind tools like ChatGPT) from OpenAI, Anthropic and similar providers to your product
- Chatbots and AI assistants for your website, WhatsApp and social channels
- AI search, recommendations and personalisation built on your existing catalogue or content
- Structured output, such as function calls and JSON formats, that the rest of your app can trust
- Choosing a model on ability, cost and speed, not just picking the newest one
Keeping AI features reliable
- A plan for what the feature does when the model is wrong, slow or unavailable
- A person's approval before anything that cannot be undone, planned in from the start
- Answers based on your real data, not on what the model half remembers
- Cost and speed tuned to real usage, not a demo's traffic
- Monitoring and alerts, so a silent failure is caught the same day, not months later
Working well with your team
- Working inside your existing product and tech stack, not a side service nobody else touches
- Pointing you to a specialist role, or a scoped PixelCrayons AI project, when the job needs one
- Code review taken seriously, not rushed through before merging
- Notes that let an engineer without AI experience maintain the feature after handover
- Clear reports on what shipped, what runs on its own and what still needs a person
In practice
What an AI developer
does once the demo is over.
Practical notes for briefing, interviewing and working with the person who puts AI inside your product.
Most of the week is not writing prompts
The visible part of an AI feature is a prompt and a response. The real work sits around it. In a typical week they build an evaluation set, a list of real user inputs to test against. They check what changed when a provider updates a model. They tighten the code that turns model output into something your app can store. They also chase answers that looked fine but were wrong. Expect changes to logging, retries and database code more often than to prompts. If every update is about a cleverer prompt, ask what is being measured, and against which examples.
Interview questions that show real AI experience
Ask the candidate to walk you through an AI feature they shipped, and what broke after launch. Strong candidates name specific failures. One is a badly formed response that crashed a parser. Others are a model that started refusing a harmless request, or a cost spike from a loop nobody capped. Ask how they knew the feature got better or worse between releases. A good answer names an evaluation set and a way of scoring it. A weak answer names a model. Then ask what they would refuse to automate in your product. Someone who can't name anything hasn't thought about your users yet.
Have your data and your limits ready
Before the first day, gather what the feature will answer from. That means help articles, product records or documents, with a note on which are out of date. Collect real inputs users will send, including the awkward ones. Decide who holds the provider account and billing. Set a spending limit before anyone starts testing. Agree which data may leave your systems at all, since that rules some providers in or out. Settle these on day one, and the first week goes on building, not waiting.
Why AI hires go wrong
The common failure is a brief that says "add AI" without saying what a correct answer looks like. The developer then aims for what impresses in a meeting, and the feature drifts from what customers need. The second failure is treating the model as the only moving part. Your data changes, users find new wording, and providers retire model versions. Without monitoring, the feature gets worse quietly. The third is letting the model act alone where it shouldn't, such as sending emails or changing records unchecked. Write down what success looks like, what must never happen, and who reviews unusual cases.
Who they work with
An AI developer rarely works alone for long. Your backend team owns the APIs and data the feature reads. Agree early who changes the database when the feature needs a new field. Designers decide how the screen shows that the AI is unsure. That could be a confidence note, a prompt to double-check, or a route to a person. Support staff often see bad answers first. Give them a simple way to flag one, with the input attached. Product owners set the line between what the feature decides and what it only suggests. Name one person on your side who signs off that line.
When this is the wrong hire
Sometimes the task is moving data between tools when something happens. Then a workflow automation build is usually simpler to maintain than custom model code. If your content is scattered, contradictory or out of date, the first job is cleaning it up. An AI developer would spend weeks on that under the wrong job title. If you need a model trained from scratch on specialist data, that is research work with different skills. And if nobody on your side can say what a good answer looks like, wait until someone can. This hire works best when the problem is already defined.
How it works
How hiring works,
with one contact throughout.
Start
Brief and a call
We sign an NDA, and you talk PixelCrayons through the product, the AI feature and the gap.
Once the brief is complete
Proposal and interview
We confirm when your proposal will arrive. ValueCoders names the engineer whose track record fits. You interview them directly before anything is signed.
Your decision
You sign off
You confirm the scope, the payment and the access we need. Nothing starts before this.
Typically 2 to 3 business days later
The engineer starts
Once they have code and API access, they review your product and data and join your stand-ups.
Every month
Scale up or down
Add a specialist when the feature needs one, or step down once it ships. The same PixelCrayons account team handles it throughout.
You make requests, give approvals and see the weekly review in your Prism workspace. Each decision is written down with the result it was meant to bring. See how Prism runs the work →
Get a Proposal
Meet the people who will do the work before you sign
Why through us
Why hire through us:
one contact and the right engineer.
PixelCrayons defines the AI role and manages your account. ValueCoders supplies the engineer. You deal with one contact and get the right builder. It is always clear who answers for the feature.
Vetted on AI features in live products
Every engineer we propose has taken an AI feature live before yours. They are vetted against ValueCoders' own delivery standards. A demo shows the feature when everything works. A track record shows what it does on the day the model fails.
One point of contact for everything
PixelCrayons scopes the AI role and writes the proposal. One PixelCrayons team then handles escalation, billing and status. A ValueCoders engineer builds the feature.
Honest advice on the right route
You hear early if the job needs a different specialist role. You also hear if it is really a scoped project for our own AI services team, not a hire. We never stretch a generalist to cover work they can't do.
ValueCoders named openly
ValueCoders is named as the team delivering your AI engineer. That holds on this page and for as long as the work runs. It stays clear who writes the model code long after the proposal is signed.
Side by side
Hiring on your own,
compared with hiring through us.
An in-house hire is worth it once the AI feature becomes core, ongoing product work, not a one-off build. We'll tell you plainly if that is where you are. Most feature work starts smaller, or fits our own scoped AI projects better than a hire.
| Hiring it yourself | Through PixelCrayons | |
|---|---|---|
| Time to a working feature | A full recruiting cycle of sourcing, interviews and notice periods, then a prototype that isn't ready for live use | Eligible work can typically start two to three business days after scope, payment and required access are confirmed |
| Vetting | A demo that impresses in the interview. Problems under real use show up after launch | A track record on real AI features in live products, checked against ValueCoders' own standards |
| Management work | All yours: recruiting, then checking every way each feature can fail | PixelCrayons' account team handles the day-to-day contact; you review the work and set priorities |
| Number of suppliers | However many agencies or freelancers it takes to cover the gap | One proposal and one point of contact, whichever engineer is assigned |
| Risk when it doesn't work | A feature that impressed in the demo fails quietly once live, with no monitoring to catch it | If the fit is wrong, we propose someone else; leaving takes a handover call with failure notes, not a negotiation |
Related reading
All articlesWho is accountable
The people responsible
for your work.
Saundaraya Gupta
Technical Manager
Brings technical work, client updates and project management together, so work moves smoothly from brief to launch.
LinkedIn →Every engagement
A named coordinator and escalation contact
Know who coordinates your engagement, who owns the work and how to escalate an issue.
All engagements. Roles may be combined and vary with your engagement.
Before you sign
Our commitments
Each one says where it applies and links to its full terms.
Time-zone overlap
At least four hours a day inside your core working hours. Two hours plus a daily written handover for the US West Coast.
Managed specialists only; not a staffing promise for project teams.
Full termsClear IP & Ownership Terms
Your materials remain yours. Bespoke deliverable rights, licences and handover are agreed before work starts.
All engagements.
Full termsClear Delivery & Escalation Ownership
Know who coordinates your engagement, who owns the work and how to escalate an issue.
All engagements. Roles may be combined and vary with your engagement.
Full termsWhy not just hire a freelancer?
A freelancer can be the right choice for a single, well-defined task. We are set up for work that needs an accountable team: a named coordinator, delivery reviewed by QA and a senior lead before release, and continuity arrangements written into the engagement. Confidentiality, ownership and escalation terms are agreed in writing before work starts.
How does time-zone overlap work?
Your engineers work at least four hours a day inside your core working hours. We set the window with you before the engagement starts and hold it for as long as the engagement runs. For the US West Coast the live overlap is two hours each morning, with a written handover at the end of every Indian day. We do not run night shifts: engineers who work nights leave quickly, and keeping the same people on your team matters more to us than a longer overlap.
Can we try you before we commit?
For eligible managed specialists, yes: up to 14 calendar days or 80 logged working hours, whichever comes first. Stop within it and eligible trial hours are free; continue and they're billed at the agreed rate. Unpaid trial work stays ours. Project work and other roles get a paid pilot with scope, acceptance criteria, duration and fee agreed first.
What if we want to stop?
Cancellation, notice and any renewal terms are written into your proposal or statement of work before you accept it. If an engagement ends early, we hand over completed, paid-for work and list any unfinished work separately. For an eligible specialist trial, you can stop within the trial window and pay nothing for eligible trial hours.
How we handle claims, credentials and your data: group credentials, dated ratings, how case figures are signed off, client permissions and data handling.
How we vet
How we vet an AI developer
and what to ask them.
ValueCoders proposes engineers vetted on AI features in live products. Your interview is the second check. These five questions show whether a candidate builds real features or only demos.
| Ask about | A strong answer | A weak answer |
|---|---|---|
| An AI feature they shipped, and what broke after launch | Specific failures. A badly formed response that crashed a parser. A model that started refusing a harmless request. A cost spike from a loop nobody capped. | The launch, and nothing after it. |
| How they knew the feature got better or worse between releases | An evaluation set built from real user inputs, and a way of scoring it. | The name of a model. |
| What they need from you before the first day | The documents the feature should answer from, and real user inputs, including awkward ones. Also a spending limit, and a decision on which data may leave your systems. | Model access, and nothing about your data or your limits. |
| What the feature does when the model is wrong, slow or unavailable | A plan for each kind of failure, plus monitoring and alerts so a silent failure is caught the same day. | A cleverer prompt, with nothing said about what is measured. |
| What a correct answer looks like in your product | Questions back to you: what success looks like, what must never happen, and who reviews unusual cases. | Starting work on a brief that says "add AI" and never defines a correct answer. |
Moving data between tools when something happens is usually simpler as a workflow automation build. A defined AI feature with an end date often fits our own AI services better than a hire.
Questions
Frequently
asked.
ValueCoders, our sister company, employs them. The AI engineer you interview and work with is on ValueCoders' team. PixelCrayons scopes the role, writes the one proposal and stays your contact throughout. We say so openly here and during the work, and never present their engineers as ours.
It depends on what you need. A hire through ValueCoders fits when you want a person joining your team long-term. A defined AI feature project with a clear scope and end date often fits our own AI services (/ai) better. We'll tell you on the first call which one fits.
No, though they are related. This page is for hiring someone to build AI features in your product. That covers LLM integration, chatbots and AI search. Workflow automation (n8n, Zapier, Make) has its own hire page. So do prompt design and testing, and retrieval or knowledge systems. We'll point you there once scoping makes the need clear.
One account team handles the whole relationship. The proposal names ValueCoders and its part in delivering your AI engineer. Escalation, billing and status updates all come through the PixelCrayons account team you signed with.
Tell us early, and ValueCoders proposes a replacement. The new engineer gets the design notes and failure decisions the first engineer kept. So a switch costs days, not a restart.
Get one proposal
with the right engineer for the work.
Tell PixelCrayons about the product and the AI feature you have in mind. We scope the role and stay your point of contact throughout. Our sister company ValueCoders delivers the engineer under a written proposal. You interview the actual person before anything is signed. If a scoped PixelCrayons project fits better than a hire, we'll say so on the first call.
Interview before signing · One account team
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