• Product-Minded Collaboration: Partner closely with Product Management to shape the roadmap and define what actually gets built. You won't just be handed technical specs; you will actively collaborate to understand customer pain points and engineer the best possible solutions. • Build Mission-Critical Systems: Design, develop, and deploy fault-tolerant, highly available distributed systems capable of handling 1,000+ TPS and securing millions of dollars in sensitive financial data with zero data loss. • Cross-Functional Partnership: Work seamlessly across organizational boundaries, partnering deeply with Product, Revenue Ops, Cloud Platform, and Security teams to ensure our payments infrastructure aligns with holistic business and operational requirements. • Optimize for Scale and Latency: Tackle complex performance bottlenecks and architect scalable solutions that maintain strict low-latency requirements for high-volume payment flows. • Drive Technical Decisions: Engage in technical trade-off discussions, drawing from past industry experience to help the team make informed architecture and design choices for high-throughput environments. • Code Quality & Review: Act as a valuable and rigorous code reviewer. Maintain a culture of code quality through comprehensive testing, automation, and adherence to rigorous engineering standards. • Full Lifecycle Ownership: Engage proactively in all phases of the software lifecycle, monitoring, alerting, and maintaining your work post-deployment to ensure absolute reliability in production.

• Design, build, and maintain scalable full-stack applications using modern technologies • Build and maintain backend services, APIs, and data models supporting customer-facing and internal systems • Develop responsive, performant front-end interfaces that deliver exceptional user experiences • Contribute to system design and architecture discussions, making thoughtful tradeoffs • Participate in the full software development lifecycle: requirements, design, implementation, testing, deployment, and support • Implement cloud-native solutions using AWS services • Develop RESTful APIs, event-driven services, and integrations supporting hardware-software coordination • Ensure systems are reliable, secure, and scalable through proper design and implementation • Experience using AI-assisted development tools to improve productivity and code quality, including tasks such as code generation, debugging, and documentation • Collaborate with Product and Design to translate requirements into technical solutions • Collaborate with firmware, IoT, and data teams on integrated system functionality • Participate in code reviews, pair programming, and knowledge sharing • Contribute to shared component libraries and promote consistency across applications

• Own the design and delivery of AI-powered automation tools that streamline creative production for enterprise teams. • Translate customer problems into scalable technical solutions in close collaboration with consultants and stakeholders. • Integrate AI models, including LLMs, text-to-image, and text-to-voice into production-grade creative tools. • Architect and build microservice-based systems that balance speed, scalability, and maintainability. • Prototype rapidly, then harden successful proofs-of-concept into reliable production applications. • Partner with designers and product managers to deliver seamless integrations with tools like Figma and Adobe. • Identify repeatable patterns across engagements and help codify them into reusable solutions and platforms.

• Design, build, and operate backend services in Python that power AI-driven products and shared capabilities. • Build and maintain resilient service integrations across internal and external systems, handling failure modes, rate limits, and interface changes. • Own ambiguous, end-to-end problems: from early design and architecture through implementation, rollout, and iteration in production. • Develop and evolve LLM-backed features and agentic workflows used in production, with a focus on reliability, observability, and real-world behavior. • Contribute to core AI platforms and enablement systems—services that your team uses directly and that other engineers can build on. • Collaborate with product managers, researchers, and other engineers across teams to turn loosely defined AI use cases into concrete, production-ready systems. • Help shape evaluation and quality strategies for AI-powered features, including building or extending evaluation harnesses, benchmarks, or feedback loops. • Act as a technical leader for the work you own—making sound design decisions, coordinating with stakeholders, and contributing to design and code reviews.