Job Overview
Remote Chief Architect of Multi-Agent Algorithmic Finance – United Arab Emirates
Location: Remote – UAE (GCC)
Employment Type: Full-Time, Remote
Compensation: Exceptional Base + Performance Incentives + Equity Participation
Overview:
The UAE seeks a Chief Architect of Multi-Agent Algorithmic Finance to design provably coherent, ontologically precise digital finance infrastructures spanning high-dimensional stochastic dynamics, distributed ledger protocols, and AI-mediated systemic governance. The role requires a rare combination of mathematical rigor, computational mastery, and ontological abstraction, enabling the formalization of liquidity networks, tokenized assets, and regulatory compliance frameworks.
Key Responsibilities:
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Develop multi-agent stochastic PDE models representing liquidity propagation, derivative pricing, and emergent systemic behaviors across GCC financial markets.
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Construct category-theoretic financial functors linking asset classes, settlement protocols, and cross-border payment architectures.
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Apply homotopy type theory for smart contract verification, ensuring invariant properties under protocol composition and operational transformations.
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Design high-dimensional tensor networks and graph-theoretic models for counterparty risk, liquidity contagion, and network topology optimization.
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Lead a transdisciplinary team of cryptoeconomists, quantitative engineers, and AI researchers, establishing rigorous simulation validation, proof-of-concept pipelines, and continuous risk monitoring frameworks.
Required Expertise:
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PhD or equivalent in Mathematical Finance, Applied Category Theory, Computational Physics, or Formal Methods in Computer Science.
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Mastery of measure-theoretic probability, stochastic control theory, Ito and Stratonovich calculus, Lévy processes, and high-dimensional Monte Carlo simulations.
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Experience with blockchain protocol design, smart contract verification, and distributed computation.
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Proficiency in Python, Rust, Haskell, C++, Julia, and associated quantitative or blockchain libraries.
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Deep knowledge of UAE Central Bank fintech regulations, cross-border settlements, AML/CFT compliance, and ISO 20022 standards.
Preferred Attributes:
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Publications in algorithmic finance, distributed systems, stochastic network modeling, or formal verification.
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Experience with multi-agent reinforcement learning for systemic risk simulation and liquidity optimization.
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Ability to translate abstract mathematical constructs into operational, scalable fintech architectures.
Impact:
Shape the UAE’s most mathematically coherent, ontologically grounded fintech ecosystem, redefining capital allocation, systemic risk governance, and AI-driven liquidity orchestration across the GCC.
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