AI Product Architect

Join Nymbus as an AI Product Architect, where you will be responsible for system design, technical integrity, and production hardening. You will work closely with a dedicated Builder and Shipper in a high-autonomy squad, and will have a hands-on role in committing production code and implementing foundational components. You will also define system and reference architectures, oversee performance and security testing, and establish deployment patterns. This is a fully remote position with a collaborative environment and various benefits.

• Assurer la conception du système, l'intégrité technique, le durcissement de la production et la cohérence entre les équipes.
• Collaborer avec les Builders et les Shippers pour définir l'intention du produit, la spécification et la mise en œuvre.
• Utiliser des outils alimentés par l'IA pour explorer les alternatives architecturales, identifier les lacunes et accélérer les revues de conception.
• Strong hands-on engineering capability and willingness to regularly commit production code in areas such as event processing, data access, integrations, observability, security, and platform services
• 5+ years of software engineering experience, including meaningful experience serving as a software architect, solution architect, or equivalent technical design authority for enterprise-grade production software
• Experience establishing non-functional requirements, automated testing standards, observability patterns, deployment approaches, and technical release criteria
• Proven ability to define and apply architecture patterns across APIs, data, integrations, testing, security, deployment, and operations
• Demonstrated ability to translate architecture into working software by designing and implementing foundational components, shared services, and technical frameworks
• Strong understanding of REST APIs, event-driven systems, data modeling, distributed-system tradeoffs, resiliency, and integration design
• Ability to balance priorities across two product squads, make pragmatic tradeoffs, and collaborate closely with Builders, Shippers, Security, and other Architects
• Ability to create practical guardrails, context, and review checkpoints that help AI- generated solutions meet enterprise standards
• At least 6 months of hands-on experience using AI-powered IDEs or coding agents such as Claude Code, Kiro, Cursor, GitHub Copilot, or equivalent tools
• Demonstrated use of AI tools for design exploration, specification, code generation, implementation, code review, analysis, or operational automation
• Willingness to experiment with tools and continuously improve AI-augmented architecture and engineering practices
• Comfort operating in a spec-first, AI-first development methodology
• Experience designing or operating enterprise multi-tenant SaaS applications in a cloud-hosted environment, particularly AWS
• A track record of modernizing or decomposing legacy applications while protecting production stability
• Experience in fintech, banking, or financial services, including core banking, digital banking, payments, cards, lending, or adjacent financial platforms
• Hands-on proficiency in two or more of Java, Node.js, Python, or React
• Experience establishing and maintaining architectural standards across multiple engineering teams
• Hands-On Leader: Builds credibility through regular production code, shared components, prototypes, reviews, and reference implementations - not authority alone
• Quality Driven: Focuses on correctness, security, resiliency, clarity, and long-term maintainability. Treats platform patterns as durable assets
• Ownership: Does not stop at design approval. Stays accountable for architectural integrity through implementation, release signoff, and production learning, while partnering with the Builder on software changes
• Architect Mindset: Optimizes for the whole platform, not a local component. Protects cross-squad consistency while helping each squad move quickly
• Experimenter: Uses AI tools to test architectural approaches, model failure modes, and improve patterns before scaling them
• High Agency: Takes ownership of system-level outcomes and drives decisions forward without waiting for heavy process. Identifies architectural gaps and closes them
• Scale Oriented: Designs for growing client volume, increasing complexity, multi-squad reuse, and operational realities from the start
• Problem Solver: Thrives in ambiguity. Frames complex problems clearly, explores tradeoffs, and converges on practical approaches quickly