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Dedicated AI Engineering Pods

Hire AI Engineers Who Ship to Production

A dedicated pod of pre-vetted AI engineers, running inside your tools and workflow, with US-hours overlap. Operational in approximately three weeks at materially lower cost than onshore hiring.

500+ engineers|~3 weeks to start|You own all IP
US-based delivery

MetaSys is headquartered in Missouri and serves companies across the United States from offices in the US, UK, and Pakistan. Pods operate in US time zones with 4 to 6 hours of real-time daily overlap. Our data handling practices are SOC 2-aligned and HIPAA-ready, and we maintain CCPA and GDPR-aware controls throughout every engagement.

HQ: Missouri, USASOC 2-alignedHIPAA-readyCCPA-aware
Why this is hard

Hiring AI talent locally is slow and expensive. The alternatives are worse.

Most engineering leaders face the same three-way problem. Local hiring is too slow for the roadmap. Contractors fragment ownership. Generic offshore agencies deliver output with no accountability. None of those options builds the team you actually need.

Local hiring takes too long

A senior AI engineer in the US or UK takes 4 to 6 months to hire. By the time they are onboarded, your competitor has shipped. Recruiting timelines are incompatible with roadmap timelines.

Contractors fragment ownership

Freelancers own the context in their heads. When they leave, the knowledge goes with them. There is no continuity, no standards, and no one who cares about the product past the invoice.

Offshore agencies deliver output, not ownership

Most agencies hand you deliverables and disappear. The code is untested, undocumented, and incompatible with your architecture. You spend months undoing what they built.

What MetaSys builds

A dedicated pod that runs as part of your team.

The MetaSys Global Capability Center model is not a staffing desk. Engineers are embedded into your workflow, accountable to your product manager, and building against your roadmap. The difference is operational continuity, not headcount numbers.

Pre-vetted, not randomly staffed

Every engineer passes a technical screen before you meet them. You interview the final shortlist and approve every hire. No surprise substitutions after signing.

Your tools, your standards

The pod runs inside your repo, your CI pipeline, your issue tracker. They follow your code-review standards and attend your standups. They are your engineers, not ours.

US-hours overlap built in

Pods are structured to overlap US East or West Coast hours by 4 to 6 hours daily. Real-time collaboration, not async handoffs.

Operational in approximately three weeks

From signed agreement to first standup is typically 15 to 21 days. That includes candidate selection, equipment provisioning, toolchain access, and onboarding sprint.

Materially lower cost than onshore

A MetaSys AI engineer costs 40 to 60 percent less than a comparable US or UK hire when you include salary, benefits, taxes, and recruiting overhead. No placement fees.

Scale 5 to 500+ without friction

Start with a five-person pod, scale to fifty engineers, or build an entire capability center in Pakistan. The infrastructure, HR, and compliance are already in place.

How a pod starts

From agreement to first commit in three weeks.

Every pod follows a fixed provisioning sequence. There are no surprises, no delays from undefined processes. This timeline has been compressed through 76+ production deployments.

01
Day 1-3

Scope and role definition

We run a working session to define the pod structure, required specializations, tech stack, and working hours. You get a staffing plan and timeline within 72 hours.

02
Day 3-10

Candidate sourcing and screening

Our talent team sources from a pool of 500+ vetted engineers. Every candidate is assessed technically before you see a profile. You interview the shortlist and make the final call.

03
Day 10-18

Offer, onboarding, and toolchain setup

We handle offers, equipment, VPN, and credentials. Your security team approves access. Engineers land with your dev environment already configured.

04
Week 3

Onboarding sprint

The pod runs a structured onboarding sprint: codebase walkthrough, architecture review, and first tickets. By end of week three they are committing.

05
Ongoing

Steady-state delivery

The pod runs as part of your team. Sprints, standups, retros, and code reviews happen inside your workflow. A MetaSys delivery lead flags blockers and handles HR so you do not have to.

500+Engineers across AI, data, and cloud
~3 wksAverage time to pod operational
76+Production AI systems shipped
2019Building dedicated teams since
Client perspective

What clients say about working with a MetaSys pod.

"MetaSys gave us a team that felt like our own engineers from week one. They were in our standups, our Jira, our Slack, pushing code the same week they started. The cost difference versus US hiring is substantial, but the bigger benefit was speed. We were shipping features in month one instead of month four."

Nick Burton

Legacy Wealth Holdings, US

Common questions

Questions before you commit.

Most clients have the same five questions before they start. Here are direct answers. If yours is not here, a 30-minute call will answer it.

Start the conversation

Ready to build your dedicated AI team?

Tell us what you are building. We will scope the right pod size, specialist mix, and timeline for your roadmap.

30-minute call, no commitment. Most clients hear back within one business day.