AgilityFeat added a fourth Builder Pod. Pod Vector is a mobile AI development team focused on products where AI and real-time communication have to work together under real device constraints: battery, memory, latency, offline behavior.
If you’re trying to hire mobile AI developers right now, you’ve probably noticed most of what comes up is job postings or solo freelancers. Pod Vector is neither.
A Builder Pod is AgilityFeat’s model for short, high-stakes engagements: two senior nearshore engineers, full-time, plus up to four on-call specialists brought in as the work demands. Each pod is a stable, pre-formed unit with shared workflows already in place, so there’s no ramp-up time and no assembling a team from scratch. Pods work nearshore from Latin America, real-time with US teams, and price at a flat $4,500 per week with a two-week minimum. Builder Pods are built for new product launches, MVPs, proofs of concept, and skunkworks projects, work where speed and engineering judgment both matter.
Pod Vector is the fourth named pod, joining Pod Atlas (workflow-heavy B2B apps), Pod Pulse (real-time and compliance-sensitive systems), and Pod Nova (voice AI). It’s a pre-formed, two-person team plus on-call specialists, available on a weekly retainer.
What Pod Vector Builds
Pod Vector specializes in AI-powered mobile app development where the AI has to run well on a phone, not just in a demo. That includes:
- Mobile-first AI products
- On-device AI app development (models running locally instead of round-tripping to the cloud)
- AI copilots inside mobile apps
- Consumer apps with embedded AI features
The team decides what runs on-device versus in the cloud based on the actual constraints of the feature, not a default. Iteration happens on real devices, not simulators.
Meet the Core Builders
- Fahad Mahmood, AI & Mobile Communications Architect, leads Pod Vector’s AI and real-time communication work. He has built CaaS products handling live video, P2P chat, and multi-party calls, the kind of infrastructure that has to perform reliably on a phone. He has also built LLM-driven products from scratch, including “virtual teammate” style AI features. That last part matters if what you actually need is LLM integration for mobile apps rather than ground-up ML engineering. Most teams searching for a mobile AI developer are closer to that second case than they realize.
- Ricardo Merino, Full Stack Engineer / Real-Time Systems, covers the backend and real-time plumbing that mobile AI features depend on. He has 10+ years building and supporting platforms across telecommunications, healthcare, and IT, with deep experience in Node.js, GraphQL, WebSockets, and WebRTC infrastructure through MediaSoup and Janus. On the frontend, he works in React and Next.js.
Tech Stack
Swift, Kotlin, React Native, Flutter, Core ML, TensorFlow Lite, on-device inference, LLM integration, spec-driven development, agentic AI.
Add-on specialists join part-time as needed: DevOps, iOS/Android platform specialists, UX/product design, and QA.
Ready to Build?
Pod Vector runs on the same terms as every AgilityFeat Builder Pod: $4,500 per week, flat rate, with a two-week minimum to hold the slot and week-by-week extensions after that.
If your roadmap includes an on-device AI feature, an LLM-powered copilot, or a mobile app that needs AI and real-time communication working together, this is the pod for it.
