Position Summary
We are seeking a Senior AI Engineer / AI Solution Architect to own the architecture and evolution of an AI-native Payments Operating System. This role will map end-to-end payment operations, identify automation opportunities and capability gaps, define the target architecture, and establish a pragmatic roadmap that delivers near-term value while enabling long-term platform modernization. The role requires a strong combination of Payments domain knowledge, enterprise architecture, AI platform design, integration strategy, governance, and stakeholder leadership.
Key Responsibilities
- Assess end-to-end Payments operations, including reconciliation, routing, settlement, reporting, controls, audit, exceptions, and incident management.
- Identify manual effort, operational bottlenecks, control weaknesses, integration failures, data gaps, and architecture complexity.
- Define a prioritized Payments AI and automation roadmap based on business value, risk, feasibility, scalability, and ROI.
- Design the target AI-native Payments Operating System, including agent architecture, orchestration, data pipelines, model access, integration, controls, reporting, and observability.
- Design an agentic Payments layer that operates alongside the current technology stack and supports gradual migration toward a future-state platform.
- Define patterns for AI gateways, model selection, prompt and agent registries, RAG/knowledge services, workflow engines, human approval, and auditability.
- Evaluate and simplify the existing Payments technology landscape, reducing duplication and improving interoperability.
- Ensure architecture incorporates security, data governance, model risk, explainability, resilience, privacy, and regulatory controls by design.
- Lead architecture reviews, proof-of-value initiatives, technical standards, reusable frameworks, and platform capability development.
- Represent Payments within the AI Center of Excellence and align with enterprise AI, data, cloud, security, and governance strategies.
- Communicate architecture, investment choices, risks, and roadmaps to engineering leaders, business stakeholders, risk, compliance, and executives.
- Mentor engineers and provide technical leadership from discovery through production optimization.
Required Experience
- 10+ years of software engineering, solution architecture, enterprise architecture, or platform engineering experience.
- At least 3 years designing Generative AI, LLM, machine-learning, or intelligent automation solutions.
- Demonstrated experience leading architecture for enterprise-scale transformation programs.
- Strong Payments or Financial Services experience, ideally involving payment processing, reconciliation, settlement, ledgers, routing, or operational controls.
- Experience defining target-state architecture, transition architecture, technology roadmaps, and implementation governance.
- Experience engaging senior business, engineering, risk, compliance, audit, and executive stakeholders.
Mandatory Technical and Architecture Skills
- AI architecture: LLM platforms, multi-agent systems, tool calling, RAG, embeddings, vector stores, model gateways, evaluation, and guardrails.
- Agent orchestration: Spring AI, LangGraph, LangChain, MCP, Semantic Kernel, AutoGen, or comparable frameworks.
- Enterprise architecture: microservices, event-driven architecture, API strategy, integration platforms, domain-driven design, and distributed systems.
- Payments architecture: transaction flows, reconciliation, settlement, payment routing, ledger interaction, exception handling, and audit controls.
- Platform architecture: Kubernetes, cloud platforms, Kafka/event streaming, API gateways, CI/CD, observability, security, IAM, and data pipelines.
- Governance: risk tiering, data classification, model risk, access control, traceability, explainability, human oversight, and audit logging.
- Roadmapping: value assessment, architectural trade-offs, dependency management, phased migration, cost modeling, and ROI measurement.
Preferred / Nice-to-Have Skills
- ISO 20022, SWIFT, ACH, real-time payments, card networks, merchant acquiring, payment gateways, or treasury operations.
- PCI DSS, SOC 2, model risk management, responsible AI, privacy regulations, and banking control frameworks.
- TOGAF, cloud architecture, security, or payments-related certifications.
- Experience establishing AI Centers of Excellence, engineering standards, reference architectures, or reusable platform services.
- Experience balancing legacy modernization with incremental delivery and measurable business outcomes.