Pre-vetted AI engineers who build LLM features, RAG, agents and ML models, ready to join your team within 48 hours.
Stack we work in
Figures as of Oct 2026
Trusted by
Our AI and ML engineers build LLM applications, retrieval-augmented generation (RAG) over your documents, AI agents that call your APIs, and machine learning models trained on your data.
They take the work from prototype to production, with evaluation, guardrails, monitoring and MLOps. They join your team in your time zone, tools and process, starting with a 15-day free trial.
Engineers with production LLM and ML experience are scarce, and a long search delays the roadmap.
A demo works on a few examples, but nobody has built evaluation, guardrails, monitoring and cost control around it.
A plain LLM call guesses. Useful answers need retrieval over your documents, access rules and a way to measure quality.
Without MLOps, a model is trained once on a laptop and nobody notices when its accuracy drops.
Outcomes
Builds LLM features into your product with hosted or open models.
Grounds answers in your documents and data.
Builds multi-step agents that use tools and hand off to people.
Trains and ships models for prediction, classification and recommendation.
Keeps models reliable after launch.
Internal assistants that answer staff questions from policies, manuals and tickets, with links to the source.
Assistants that resolve common requests, draft replies and hand complex cases to your team.
Fields pulled from invoices, contracts and forms into your systems, with checks on low-confidence results.
Agents that read requests, look up records through your APIs and complete routine steps with human approval.
Demand, churn, risk or lead scoring models served to your apps and dashboards.
Smart search, summaries, recommendations and classification added to your web or mobile app.
Built with
Built with
Built with
Built with
Featured case study
Every business already owns the sensor network it needs. CCTV records everything and tells you nothing — until someone reviews the footage, usually days after the loss.
Read the case study
We review your requirements, stack and goals, and recommend the AI engineer roles and seniority your project needs.
You receive Role and skills plan
We shortlist pre-vetted developers who match your stack and time zone. Each has passed a technical evaluation on the models, frameworks and tools your project uses, a communication check and a team-fit review.
You receive Developer profiles
You interview the shortlisted developers and choose. Nothing starts until you are happy.
You receive Your chosen developer
The developer joins your tools, repositories and ceremonies. The first 15 days are a free trial, so you judge the work in your real project.
You receive Developer working in your workflow
The developer delivers in agile sprints with daily progress reports, and you scale the team up or down as needs change.
You receive Daily reports and sprint releases
Tech stack
AI and machine learning
Databases
Backend and APIs
Languages
Cloud and DevOps
Hiring models
Pick the commitment that fits your roadmap, and change it as your needs change. Every model works in your time zone, with clear pricing agreed after a call and no hidden costs.
An AI engineer who works only on your project, full working days, as part of your team.
Half-day availability for steady work that does not need a full seat.
Pay for the hours used, for fixes, audits, small enhancements and short spikes of work.
A fixed scope, timeline and price, delivered by a team we manage end to end.
A cross-functional squad of developers, QA, a designer and a project manager or scrum master, sized to your roadmap.
Free trial
Interview the shortlisted developers, choose one, and judge the work in your real project during a 15-day free trial.
More roles
We also provide data engineers, BI developers, web, mobile, QA and DevOps specialists. See every role you can hire.
It depends on the role, seniority and hiring model. Full-time and part-time developers are billed monthly, hourly work is billed for the hours used, and project-based work is paid by milestone. After a short call we share developer profiles and a clear monthly or hourly rate, with no hidden costs. As a guide, our rates range from $30 to $70 per hour (USD), depending on seniority and skills, and full-time monthly engagements cost less per hour than hourly work. We confirm your exact rate after a short call.
Pre-vetted developers can join your team within 48 hours of you selecting them.
Yes. We align developers to your preferred time zone and working hours so you can collaborate in real time.
The 15-day trial is free. Use it to assess the developer's skills, code quality, communication, delivery and fit with your agile process. If you are satisfied, you continue the engagement; if not, you can stop with no obligation.
We sign an NDA, use data encryption, secure storage and regular security audits, and follow GDPR requirements. Equitysoft is ISO 27001 certified. You own all code, data and IP, with no lock-in.
Tell us and we will replace them quickly, so your project stays on track.
You set the priorities and direct the work, just as you would with your own staff. You receive daily progress reports and talk to the developer through email, video calls, chat and your project management tools. We take care of employment, equipment, attendance, performance support and replacements.
Every candidate passes a technical evaluation on the models, frameworks and tools your project uses through practical tasks and code review, not just a CV. We also check spoken and written English, how clearly they explain technical decisions, and their experience with agile ceremonies, code review and remote product teams. You then interview the shortlist yourself.
All three. They build with hosted models such as OpenAI, Claude and Azure OpenAI, and with open models run through Hugging Face or Ollama when data must stay on your own infrastructure. They pick a model after testing it on your own examples, and structure the code so the model can be changed later.
They ground answers in your data with retrieval, build an evaluation set from real questions, and measure answer quality before and after each change. They add guardrails, logging and monitoring, so problems show up in dashboards rather than in user complaints.
Book a call to discuss your use case, data and stack. We will propose AI engineers you can start trialing within 48 hours.
