Staff Software Engineer - AI Applications

Plaid In The Fintech Ai Ecosystem Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. We believe consumers should be able to understand and manage their financial life through conversational AI interfaces using natural language. We believe consumers should have peace of mind with a trustworthy consent and authorization manager when agents shop for them. We believe identity verification and financial fraud prevention in AI-powered products should feel seamless and embedded for the end users. The list goes on. The most important AI companies, major fintechs, and customer agent platforms are actively trying to integrate Plaid into AI-powered products and solutions they build. Our early experiments in building AI agents for customer experience are paying off with huge business value. For example, our homegrown AI-powered customer support agents resolve a significant proportion of customer questions and issues within seconds, which would otherwise have required humans hours to work on. This is just the beginning and there is so much more we could do. The Ai Applications Team You will have the opportunity to join as one of the founding members of this newly formed team that is dedicated to consolidating and rapidly scaling our successful bets so far, and grow with the team in our quest to accelerate Plaid's transformation into an AI-first company. In this role you will lead projects that enable and scale our business with our largest AI customers and partners, starting with personal finance use cases and expanding into many others; examples include: Develop and evolve the preferred integration pattern for Plaid with AI providers - from API adaptations to building the official Plaid MCP Servers, and beyond Redefine how Plaid's consumer link experience embed into conversational interfaces in the most seamless way Architect the trust layer for the future of agentic commerce that will become the industry standard Additionally you will be expected to scale and extend our existing successful bets on AI-powered customer experience; examples include: Make the next step-function improvement in our homegrown customer support agent - land our multi-turn and multi-agent system that powers a truly delightful experience for our customers; define how to scalably run offline evaluation for complex multi-turn open-ended tasks; research and prototype how Human-In-The-Loop - Reinforcement Learning (RLHF) can power an insights flywheel; pioneer the architecture for customer-specific long-term memory, etc. Extend our agentic system to support other critical parts of the customer journey, starting with areas with the highest ROI - top-of-funnel product recommendation, customer onboarding and risk diligence, customer activation and assistance for faster productionization, as well as upselling and cross-selling of Plaid products You will have a front row seat to all the latest industry developments. Over time, with the skills and experience you develop and hone on this team, you can become an influential voice in defining where AI > Fintech will be heading longer term. Responsibilities Design, develop, and maintain scalable backend services and APIs, as well as intuitive, high-quality frontend applications that bring those systems to life. Work with other AI engineers, software engineers and machine learning engineers to architect, design and implement GenAI-powered products and features Collaborate across functions to understand user needs, propose and implement AI-powered solutions where they're expected to have the highest impact Design and execute rapid experiments to push the boundaries on potential business impact from emerging AI capabilities, with a focus on minimal viable testing approaches Balance creative exploration of possibilities with rigorous evaluation of technical feasibility, product potential and business impact Requirements Experience building backend services and working with microservices or service-oriented architectures Hands-on experience working with LLMs to build products and shipping them to product with iterating with real user feedback - including but not limited to: Prompt engineering Fine-tuning Retrieval augmented generation (RAG) Semantic search - vector database and embedding models Agent orchestration framework Evaluation and monitoring framework of open-ended tasks Streaming and SSE Common UX and design patterns for GenAI-powered products Strong debugging and monitoring experience for production systems Ability to deeply understand customer and user needs through user research and rapid experimentation - be your own technical PM Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility), which is critical for driving 0 ->1 projects Extremely curious and passionate about working in GenAI applications space Nice-to-Haves Experience training and/or serving ML models in production, or fine-tuning LLMs for domain-specific use cases Comfortable operating in privacy/PII-sensitive environments and applying compliance mitigations Working knowledge of HTML, CSS, JavaScript, and modern frontend frameworks or libraries, with comfort building user-facing experiences Plaid