AI Engineer

About the role

We are seeking a full-stack AI Engineer who treats artificial intelligence not just as a product feature, but as their primary engineering partner. In this role, you will leverage advanced AI coding assistants, agentic workflows, and large language models to radically accelerate the design, engineering, and deployment of our core financial systems from the database layer up to native mobile and web interfaces.

You are a highly capable engineer who uses AI to multiply your output, rapidly prototyping system architectures, generating complex backend logic, scaffolding cross-platform UI components, automating test suites, and streamlining modern GitOps CI/CD pipelines. Because we operate in a highly regulated financial environment, you will serve as the critical "human in the loop," rigorously auditing AI-generated code and deployment manifests for security vulnerabilities, UI/UX consistency, deterministic reliability, and strict compliance with our data privacy standards.

Key responsibilities

• Extensively use enterprise-grade AI tools (e.g., GitHub Copilot Enterprise, Cursor, Claude) to write, refactor, and optimize clean, highly scalable code across native mobile apps (iOS/Swift, Android/Kotlin), web frontends (H5/Svelte), and backend services (Python, Go, or Node.js)
• Direct AI agents to write, optimize, and maintain CI/CD pipelines, Kubernetes manifests, and Helm charts to ensure seamless, automated deployments across staging and production environments
• Use LLMs to quickly convert business requirements into functional full-stack prototypes, mobile UI layouts, API contracts, and database schemas before writing production-grade implementations
• Direct AI agents to instantly generate exhaustive unit tests, end-to-end integration tests, and semantic code reviews to maintain flawless financial transaction processing and seamless user experiences on all devices
• Partner with LLMs to brainstorm distributed system architectures, evaluate technical trade-offs, and generate comprehensive technical blueprints for both client-side mobile/web applications and resilient microservices
• Ensure that while AI accelerates the engineering process, all critical financial logic, ledger updates, and transaction processing rely on strictly deterministic, rules-based engines
• Scrutinize all AI-generated mobile, web, and backend code for security flaws, memory leaks, accessibility issues, and logic errors, ensuring zero hallucinations or vulnerabilities make it into the production codebase
• Establish safe patterns for using AI tools within a zero-trust architecture, ensuring proprietary source code, Personally Identifiable Information (PII), and Payment Card Industry (PCI) data are never exposed to public AI models