Staff Augmentation · AI-Enabled Developers · ML Engineers
AI-enabled engineering teams, from a company that runs AI in production.
Add developers who use AI to move faster — and review every line it writes — plus ML specialists who’ve shipped real systems. They join your team, work in your process, and come from a company that builds and runs its own AI products.
- AI suggests a changeOnly tools your policy approvesDraft
- Engineer reviews every lineAI output is a first draftReviewed
- Your code review and testsYour normal process, unchangedApproved
- Merged into your repositoryHowever it was writtenYours
- Human review on every change
- Only the AI tools you approve
- Your code stays yours
- AI built in-house, not just sold
Two ways to add engineers
Engineers who build with AI — and engineers who build AI
Staff augmentation and offshore developer teams in two forms — and every engineer comes from a company that builds its own AI products.
AI-Enabled Developers
Full-stack, .NET and Java developers who use AI coding tools every day — only the tools your policy approves, with human review on every change and your code kept yours.
ML & Data Specialists
ML engineers, data engineers and MLOps specialists who’ve worked on AI systems in production, not just in notebooks.
How it works
From request to working engineer
- 1Tell us the role, stack and your AI tool policy.
- 2Review profiles.
- 3Interview the engineers yourself. You choose who joins.
- 4Onboard. They work in your tools, your standups and your process.
- 5We manage the rest — employment, payroll and equipment.
Why AI-enabled isn’t enough
AI writes code fast. Someone still has to stand behind it.
Most developers now use AI tools, and most of them don’t fully trust what those tools produce — for good reason. AI-generated code often looks right and isn’t, and security testing keeps finding flaws in it. Our engineers treat AI output as a first draft, not a finished change.
Reviewed.
Every AI-assisted change is checked by the engineer who made it, then goes through your normal code review.
Within your policy.
Only the AI tools you approve. If your policy says no AI on your codebase, our engineers work without it.
Yours.
The code belongs to you, however it was written.
Why our engineers know AI
We don’t just place engineers. We build and run AI ourselves.
We build our own AI products, including Aalam Doc AI, and we take client AI projects from proof of concept to production. Our engineers work alongside that experience every day — which is why their AI skills are real, not a line on a résumé.
FAQ
Questions buyers ask us
Something we haven’t covered? Tell us the role, the stack and your AI tool policy, and ask us directly.
Tell us the role you need →What exactly does Aalam do?
Two things. Most of our work is staff augmentation: we place engineers into US engineering teams, where they work to your direction inside your process. The rest is AI and ML projects we build and deliver ourselves, which is where the engineers who understand this work come from.
What does “AI-enabled” actually mean here?
It means our engineers use AI coding tools on client work, under a written policy, and can explain how. It does not mean we sell AI agents or claim a productivity percentage. Which tools, whether your code reaches a model, who reviews the output and who owns it are all published on our AI usage policy page.
Where are you based and how long have you been doing this?
Chennai, India, since 2016. We are an LLP of 11 to 50 people. We are not a 600-person body shop and we do not pretend to be one.
Need engineers who work well with AI?
Tell us the role, the stack and your AI tool policy. We’ll tell you honestly whether we have the right people.