Hire developers · 17 technologies
Engineers screened by an engineer.
Most technical recruitment fails at the same point: the recruiter cannot tell a good answer from a confident one. Every candidate here has had a real technical conversation with someone who has done the job, and you get written evidence per competency rather than a CV dump.
Front-end
The part your users actually touch.
Front-end
React
The default choice for new front-ends, and the stack with the widest candidate pool — which cuts both ways at interview.
- Front-end engineer (React)
- Full-stack engineer (React + Node)
- Senior / lead front-end engineer
- UI engineer with design-system ownership
Front-end
Angular
Still the standard in enterprise and regulated environments, where its opinionated structure is the point rather than the cost.
- Angular developer
- Senior Angular engineer
- Front-end lead on an enterprise application
Front-end
Vue
A smaller pool than React, generally a higher median, and a common choice for teams that wanted React's flexibility with more structure.
- Vue developer
- Full-stack engineer (Vue + Laravel or Node)
- Senior front-end engineer
Front-end
TypeScript
Hired as a discipline rather than a framework — for teams whose problem is type safety and shared contracts across a codebase, not any one UI library.
- TypeScript engineer
- Full-stack TypeScript developer
- Platform or tooling engineer
Back-end
APIs, services and the data underneath them.
Back-end
Java
The stack most likely to be running something that cannot be switched off, which makes the screen as much about operational judgement as language.
- Java backend engineer
- Senior Java / Spring Boot engineer
- Backend lead or principal engineer
Back-end
.NET
Strong in enterprise India and the UK mid-market. The live question at interview is usually how much of their experience is .NET Framework.
- .NET developer
- Senior .NET / C# engineer
- Full-stack .NET engineer (with Angular or React)
Back-end
Python
Two largely separate candidate pools — web and API engineers, and data or ML engineers. Which one you need changes the search entirely.
- Python backend engineer
- Django or FastAPI developer
- Data engineer (Python)
- ML engineer
Back-end
Node.js
Usually hired alongside a front-end stack, for teams that want one language across the codebase and shared types with it.
- Node.js backend engineer
- Full-stack JavaScript / TypeScript engineer
- API engineer
Mobile
Native and cross-platform, shipped to a store.
Mobile
iOS / Swift
Native iOS, in Swift. A smaller and more expensive pool than cross-platform, and the right answer when the app is the product.
- iOS engineer
- Senior iOS engineer (SwiftUI)
- Mobile lead
Mobile
Android / Kotlin
Native Android, in Kotlin. The deeper pool of the two native platforms in India, and the one where device fragmentation does the screening for you.
- Android engineer
- Senior Android engineer (Compose)
- Mobile lead
Mobile
Flutter
One codebase for both platforms, in Dart. Sensible when the app is content- or form-driven; less so when it leans hard on native APIs.
- Flutter developer
- Senior Flutter engineer
- Cross-platform mobile engineer
Mobile
React Native
Cross-platform for teams that already have React engineers. Hiring here usually follows an existing front-end investment rather than preceding it.
- React Native developer
- Senior mobile engineer (React Native)
- Full-stack engineer with mobile ownership
AI & Cloud
Platforms, pipelines and the engineers who run them.
AI & Cloud
Cloud engineer
The engineer who owns what your software runs on — networks, identity, deployment and the pager. The screen is about what they have operated, not which cloud is on the CV.
- Cloud engineer
- Senior cloud / DevOps engineer
- Platform engineer
- Site reliability engineer
AI & Cloud
Data engineer
Pipelines, warehouses and the modelling underneath them — the foundation that analytics and every AI feature actually depend on.
- Data engineer
- Senior data engineer
- Analytics engineer
- Data platform engineer
AI & Cloud
Machine learning engineer
Models built against a metric that matters, and the evaluation harness that says whether the next version is actually better.
- Machine learning engineer
- Senior machine learning engineer
- Applied scientist
- Data scientist (engineering-leaning)
AI & Cloud
MLOps engineer
The path from a trained model to one running in production — versioned, monitored, and rollback-able when it drifts.
- MLOps engineer
- ML platform engineer
- Senior MLOps engineer
- ML infrastructure engineer
AI & Cloud
AI engineer
LLM and agent features built on your own data and permissions, with the evaluation and guardrails designed in rather than added after.
- AI engineer
- Senior AI engineer
- LLM application engineer
- GenAI engineer
What hiring one yourself costs
Nine to fourteen weeks before anyone writes a line of code.
Sources: Cadence, How long does it take to hire a software engineer (2026); Riem.ai, Cost per hire: software engineer (2026); CB Insights, via Second Talent remote engineering cost comparison (2026). None of these is a StackHog figure — they are the cost of the alternative. Work out your own number →
The other way in
Or have us build it instead.
If the need is the work rather than the headcount, the service catalogue is the other entry point.