Chief AI Architect
Build the intelligence behind PrescientIQ — our AI-powered predictive optimization platform that transforms decision-making from reactive analytics to proactive foresight.
Where AI meets foresight
MatrixLabX is pioneering the future of intelligent optimization platforms with PrescientIQ — an AI-powered predictive intelligence system that transforms marketing and business decision-making from reactive analytics to proactive foresight.
Our mission is to merge causal AI, multi-objective optimization, and autonomous orchestration into a scalable enterprise platform that empowers leaders to predict outcomes and act with precision. We’re building systems that reason, forecast, and adapt — not just analyze.
Architect the intelligence behind PrescientIQ
As Chief AI Architect, you will be the visionary and technical steward behind PrescientIQ’s AI ecosystem. You’ll lead the architectural design, development, and deployment of next-generation AI systems that power predictive analytics, real-time optimization, and autonomous decision-making at scale.
You will bridge the gap between AI research, data engineering, and product design — architecting a platform that can interpret, predict, and act on complex multi-channel business signals in real time.
Own the architecture that turns data into foresight and autonomous action.
What you’ll lead
- ✓Architect the Core Intelligence Layer: Design and evolve the core causal AI engine for predictive insights, scenario modeling, and multi-objective optimization.
- ✓Unify Data + Model Infrastructure: Build scalable data pipelines and model-serving infrastructure across cloud and edge environments.
- ✓Integrate Causal Inference & Generative Models: Combine causal reasoning with LLMs and agentic systems for explainable, adaptive decisioning.
- ✓Drive End-to-End System Design: Oversee ingestion, training, inference, orchestration, and explainability dashboards.
- ✓Collaborate Across Domains: Translate business needs into scalable, intelligent architectures with product, DS, and engineering.
- ✓Ensure Ethical & Responsible AI: Embed fairness, transparency, privacy, and governance across the AI lifecycle.
- ✓Mentor & Lead: Develop a high-performing AI/architecture team and set standards and best practices.
- ✓Stay on the Edge: Evaluate frameworks like JAX, PyTorch, LangChain, RL, causal ML, and agent orchestration