Engineering Manager, AI Applications

Plaid•San Francisco, CA

6d•$216,000 - $367,200

About The Position

AI and intelligent systems are driving the fifth paradigm shift, following previous technological revolutions like mainframes, personal computers, the internet, and mobile devices. Plaid is uniquely positioned to become the financial data and insights backbone for AI applications and platforms in this evolving ecosystem. The explosive growth in model intelligence and increasing relevance for enterprise tasks offer a unique opportunity for Plaid to rethink from the ground up how we operate and interact with our customers for the most optimal experience. 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. You will have the opportunity to lead this newly formed team that is dedicated to 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.

Requirements

8+ years of industry experience, that includes time as a Staff-level engineer before transitioning into management.
1+ years of engineering management experience
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
Ability to deeply understand customer and user needs through user research and rapid experimentation - be your own technical PM
Track record of building and growing high performing engineering teams (either as an engineer or a manager).
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

Responsibilities

Lead a team of 4 engineers, ranging from junior to staff, developing them through clear goal setting, coaching, and feedback
Define and drive the long-term strategy and manage execution on the team, in close partnership with technical and product leaders across Plaid
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.
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
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.