"Hire AI developers" gets used two different ways, and mixing them up costs you weeks. One meaning: bring in engineers who write code against your product — model integration, RAG pipelines, agent orchestration, the plumbing that makes an AI feature ship. The other: bring in consultants who assess your AI strategy and hand you a roadmap. Both are legitimate. Only the first one gets you a working feature by next month.
This guide is about the first kind — shops and firms that put engineers on your codebase, not just a slide deck on your desk.
How to tell a staffing shop from an advisory firm
Read the engagement language on a company's own site before you ever get on a call.
- "Dedicated team," "staff augmentation," "embedded engineers" — these phrases mean the firm expects to place named people on your project, often inside your own repo and sprint process. BairesDev and Tecla both build their pitch around assembling engineering teams this way, drawing on Latin American talent pools. Innowise and TechAhead offer the same model alongside project-based builds.
- "Strategy," "roadmap," "assessment," "readiness" — this is advisory language. You'll get a report and recommendations, not a pull request. Useful before you've defined the build, not after.
- Hybrid shops exist too. Saigon Technology and ISHIR explicitly offer staff augmentation, dedicated teams, and fixed-price project work as separate options — ask which one you're buying before you sign.
Smaller shops sometimes skip the corporate vocabulary entirely and just describe what they build. Bezep Solutions, a Prishtina-based team, offers dedicated teams and team augmentation alongside fixed-price feasibility audits — read the actual service list, not just the homepage headline.
What to ask before you commit to a staffing engagement
- Who, by name, is on the team? A staffing engagement is only as good as the specific people assigned. Get names, seniority, and prior project examples — not "a team of senior engineers" as a category.
- Do they work inside your stack or hand you theirs? Some shops embed engineers into your existing repo, ticketing system, and standups. Others run the build on their own infrastructure and deliver a handoff. Neither is wrong, but they're very different working relationships.
- What's the ramp time? Staff-augmentation engineers should be productive against your codebase in days, not weeks. If a shop can't give you a straight answer on ramp time, that's a signal.
- Is there a lightweight way to start? A short paid pilot — a scoped slice of real work — tells you more about how a team actually works than any proposal call. Boutique shops like asaasin.ai, which offers a free prototype before any commitment, and other small teams on this site are generally more flexible about starting small than large firms with fixed minimum engagements.
- What happens when the engagement ends? Staff-augmentation contracts should say clearly whether you retain the code, the fine-tuned models, and any custom tooling once the engineers roll off.
Where team size changes the calculus
A boutique shop puts a small number of senior people directly on your project — you get less bench depth but more hands-on attention from people who can't disappear into a larger org chart. A large shop gives you a bigger bench and the ability to scale a team up mid-project, with more risk that the engineers on your actual sprint aren't the ones who impressed you on the sales call. Match the size to how much project-management overhead you want to own yourself.
If your project is narrowly technical — a computer vision pipeline, a specific LLM integration — filter by specialty first and size second. A large generalist shop with no computer vision case studies isn't a better bet than a boutique team that's shipped three of them.
A short checklist before you hire
- Confirm the engagement model in writing: staff augmentation, dedicated team, or project-based — not just "we'll help."
- Get named engineers and their prior project examples, not team-size claims.
- Ask for a ramp-time estimate and hold them to it.
- Start with a small, scoped, paid piece of real work before a longer commitment.
- Nail down code, model, and data ownership for when the engagement ends.
- Filter this site by specialty and company size to match the shop to your actual project shape, and check the full-stack development filter if your build needs more than just the AI layer.