Principal Architect – Money and Payments R&D

Role Overview

• Architect high-throughput distributed payment systems with strong consistency guarantees
• Design and implement EVM virtual machine infrastructure with parallel execution capabilities
• Write production-grade Solidity implementing settlement, orchestration, and atomic cross-service composition
• Optimize transaction processing for extreme load through parallelization and intelligent partitioning
• Build cryptographic protocols including zero-knowledge proofs for privacy-preserving validation
• Establish code quality standards and lead reviews across smart contracts, infrastructure, cryptography, and DevOps
• Architect cloud-native platforms with multi-region resilience and horizontal scalability
• Design unified data platforms enabling cross-system analytics and eliminating data silos
• Build Kubernetes-based orchestration with custom operators for distributed applications
• Implement GitOps workflows and Infrastructure as Code
• Create CI/CD pipelines with comprehensive testing, security scanning, and zero-downtime deployments
• Establish observability strategies with distributed tracing, metrics, and real-time alerting
• Translate payment system challenges into AI-native and agentic capabilities that modernize payment workflows and operations
• Design and implement agentic AI systems for autonomous payment orchestration, fraud detection, and real-time decision-making
• Architect AI-enabled payment rails that leverage machine learning for intelligent routing, liquidity optimization, and risk management
• Build agentic commerce capabilities enabling autonomous financial transactions and smart contract execution
• Develop AI systems that enhance payment system resilience through predictive analytics and anomaly detection
• Design multi-agent systems for coordinating complex payment workflows across institutional boundaries
• Drive adoption of AI-assisted programming tools to accelerate development velocity system-wide
• Build AI agents and custom tooling automating code review, testing, documentation, and security scanning
• Establish governance and best practices for responsible AI usage in production systems
• Lead the shift toward AI-enabled software development operations, reducing manual burden and improving code quality
• Create frameworks for AI-assisted development that scale across distributed engineering teams
• Connect AI capabilities to strategic payment system value, ensuring AI delivers measurable business outcomes
• Translate complex technical concepts into business value for executive stakeholders and policymakers
• Synthesize stakeholder pain points into validated AI-native technical solutions
• Mentor engineers across application development, platform engineering, DevOps, and AI implementation
• Lead proof-of-concept development demonstrating feasibility of emerging payment and AI technologies
• Drive cross-functional coordination across business lines, IT, security, and compliance to enable integrated AI delivery.

Requirements

• Deep knowledge of consistency models, concurrency control, transaction parallelization, and deadlock resolution
• Expert Solidity programming, EVM architecture implementation, gas optimization, security auditing, and composable contract design
• Experience implementing zero-knowledge proofs, Merkle trees, digital signatures, and blockchain-agnostic verification protocols
• Experience applying machine learning to financial systems including fraud detection, intelligent routing, risk assessment, or payment optimization
• Understanding of multi-agent architectures, autonomous decision-making systems, and AI orchestration frameworks
• Expert-level Kubernetes including operators and admission controllers; Helm charts; service mesh technologies
• Infrastructure as Code, GitOps workflows, CI/CD pipelines, distributed tracing, metrics
• Demonstrated expertise leveraging AI coding tools and building custom AI agents
• Background in high-performance financial systems with understanding of operational workflows
• Experience identifying and translating business problems into AI-native capabilities
• Understanding of consensus protocols and their trade-offs
• Knowledge of payment system modernization challenges and AI applications in financial services
• Advanced degree in Computer Science, Distributed Systems, Cryptography, Machine Learning, or related field preferred.
• Exceptional ability to communicate technical concepts to non-technical executives and policymakers
• Track record leading cross-functional teams from prototype to production in complex regulated environments
• Experience translating business requirements and operational pain points into technical architectures
• Ability to connect AI innovation to measurable business outcomes and strategic value
• Experience driving organizational transformation and technology adoption at enterprise scale
• Ability to balance innovation with pragmatism, ensuring responsible AI deployment in production systems.

Tech Stack

• Cloud
• Distributed Systems
• Kubernetes
• Ruby on Rails
• Solidity

Benefits

• Health insurance
• Retirement benefits
• Paid time off
• Flexible work arrangements
• Professional development opportunities