Most AI never ships — or ships and quietly burns money. I take AI features from prototype to production fast, then make them reliable and cheap. You get something that works, and a bill that makes sense.
Real systems I designed and shipped — across AI, voice, fintech, and data-heavy products.
I'm Maaz — an independent AI engineer. I build production-grade AI systems end to end: the agent loops, retrieval pipelines, voice stacks, sandboxes, and billing that turn a promising demo into something a business can actually run on.
I've shipped an AI website builder, real-time voice agents, a self-hosted RAG platform, a crypto exchange, and more — across AI, fintech, voice, and commerce. Deep in AI, comfortable across the whole stack.
Available for a focused engagement — an audit, a build sprint, or an ongoing fractional role.
Four ways teams bring me in — all hands-on engineering, not decks.
Ship the feature your team keeps not shipping — agents that complete real tasks, RAG that answers from your data, voice that holds a conversation.
Live but bleeding money or too slow? I cut token cost and latency and raise quality — metering, caching, routing, and evals that prove it.
The hard end — multi-step agents, sub-agent orchestration, and sandboxed code execution that stays reliable under real load.
Zero to deployed — backend, infra, data model, frontend, auth, and billing. One person who takes an idea to a paying product.
Not just AI in your product — AI in how you build it.
Parallel AI agents, orchestrated build-review-ship pipelines, and project management that actually moves throughput — the same setup I use to run several products at once.
Fan work across parallel AI coding agents — Conductor + Claude Code. Ten tasks at once, not one.
Spec → build → review → ship as one repeatable pipeline. Agents draft, you steer.
Linear set up so cycles and priorities drive real throughput, with AI in the loop.
CI/CD, automated review, QA, and deploy — tuned so shipping is fast and boring.
Scoped, outcome-priced engagements. Pick the entry point that fits.
I review your AI stack — architecture, cost, latency, quality — and hand back a prioritized roadmap of exactly what to fix, in what order.
We agree one outcome and I take your AI feature from half-working to shipped in production — code, infra, and the evals to trust it.
An embedded senior AI engineer a few days a week — for the team that needs the capability but isn't ready to hire full-time.
Tell me what you're building and where it's stuck. I'll tell you straight whether I'm the right person and how I'd approach it.
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