Loading…
Loading…
Our engineers have built and shipped for the world's leading tech companies. Get proven, AI-trained talent embedded in your team — not contractors, not freelancers. Your pod.
Hiring takes 3–6 months
We assemble pods in 5 business days
35% annual engineer attrition
Our attrition rate is just 3%
Generalist talent pools
AI-trained, domain-specific specialists
No IP or compliance coverage
ISO 27001 + SOC 2 Type II certified
We're built for AI transformation — obsessed with outcomes, not headcount.
Our engineers have firsthand experience fine-tuning models, shipping LLM applications, and deploying scalable GenAI systems — not just using ChatGPT prompts.
Every candidate passes multi-stage technical challenges, peer code reviews, and our proprietary AI scoring — so only the top 3% join the network.
Skip traditional recruiting delays. We match, scope, and deploy embedded pods in 5 business days — so you start shipping from day one, not month three.
Our engineers stay. That means accumulated domain knowledge, zero re-onboarding cycles, and consistent delivery velocity across your entire engagement.
Enterprise-grade security baked in. Every pod operates within your compliance perimeter with full NDA coverage, IP assignment, and audit-ready processes.
No 12-month lock-ins. Scale pods up or down as your roadmap evolves. You pay for execution, not bench time.
Every role is filled by engineers with 5–15 years of domain expertise.
Full-stack, backend, frontend, and mobile specialists. Production-proven across modern frameworks, cloud infra, and AI toolchains.
Specialists in LLM fine-tuning, RAG architectures, agentic workflows, and production-grade ML pipelines — not just API wrappers.
UX researchers, product designers, and design system architects who craft experiences users love — across web, mobile, and AI interfaces.
Professionals who build the data foundations AI systems depend on — pipelines, warehouses, feature stores, and analytical models.
Automation engineers who ship quality — Selenium, Playwright, Cypress, load testing, and CI/CD integration across your full release pipeline.
Infrastructure experts who build the platforms your AI systems run on — Kubernetes, Terraform, multi-cloud architectures, and zero-downtime deployments.
We map your stack, team dynamics, roadmap, and SLAs.
AI matching + human review surfaces the perfect team. You approve every engineer.
Your pod joins Slack, accesses repos, and sets up environments. Security verified.
Your pod studies the codebase, plans first tickets, and completes compliance checks.
First PRs, first deploy to staging, daily standups live. Real velocity.
Wegile assembled a 5-person AI pod within 5 business days. They were in our Slack, pushing code, and attending standups by day two. It felt like hiring full-time engineers without the 3-month lead time.
James Mitchell
CTO, ChargedUp
We needed LLM integration expertise fast — Wegile had engineers with production RAG experience deployed within two days. The quality bar is genuinely different from typical offshore vendors.
Sarah Reynolds
VP Engineering, Finova
The 7-year average tenure isn't marketing fluff. Our Wegile pod lead has been with us for 4 years now. That kind of continuity is priceless when you're building complex systems.
David Chen
Head of Product, MediSync
Get a dedicated engineering pod — assembled in 5 business days, retained for years, and priced like a subscription.