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Engineering Manager, AI Applications

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Plaid

Plaid offers a platform that enables applications to connect with users' bank accounts, facilitating a wide range of financial services. They provide tools for payments, personal finance management, credit, and more, serving clients like Moneybox, Western Union, and Affirm. Their core product is an API that provides access to a vast network of financial institutions, allowing developers to build financial products and services.

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About Plaid

Plaid is a financial technology company that enables applications to connect with users' bank accounts. It allows consumers and businesses to interact with their bank accounts, check balances, and make payments through other financial technology applications. Plaid's network connects to over 12,000 financial institutions across 20 markets, serving a global user base of over 100 million. The company provides APIs for developers to build solutions for personal financial management, credit, payments, business finances, iGaming, and property management. Key products include Auth for account verification, Link for connecting accounts, Transactions for accessing financial data, Balance for real-time checks, Assets for verifying assets, and Identity for user verification. Plaid focuses on increasing conversion, fighting fraud, and providing clean, organized financial data for smarter underwriting and other financial services.

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About the Role

You will lead a newly formed team dedicated to rapidly scaling successful AI bets and accelerating the company's transformation into an AI-first organization. You'll manage a team of four engineers, ranging from junior to staff, developing them through clear goal setting, coaching, and feedback. You will define and drive the long-term strategy for the team and manage execution in close partnership with technical and product leaders. You'll have a front row seat to the latest industry developments, and over time you can become an influential voice in defining where AI and Fintech will be heading. You'll lead projects that enable and scale the business with the largest AI customers and partners, starting with personal finance use cases and expanding into others. You'll also work to scale and extend existing successful bets on AI-powered customer experience, including improving a homegrown customer support agent and extending the agentic system to support other parts of the customer journey.

Requirements

  • 8+ years of industry experience, including 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 ship them, iterating with real user feedback, including prompt engineering, fine-tuning, retrieval augmented generation (RAG), semantic search, vector databases and embedding models, agent orchestration frameworks, evaluation and monitoring frameworks, and streaming/SSE
  • Knowledge of common UX and design patterns for GenAI-powered products
  • Ability to deeply understand customer and user needs through user research and rapid experimentation
  • Track record of building and growing high performing engineering teams
  • Ability to balance divergent thinking with convergent thinking for driving 0 to 1 projects
  • Curiosity and passion for working in the GenAI applications space

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
  • Partner with technical and product leaders across the company
  • Lead projects that enable and scale the business with the largest AI customers and partners
  • Develop and evolve the preferred integration pattern with AI providers, including building official MCP Servers
  • Redefine how the consumer link experience embeds into conversational interfaces
  • Architect the trust layer for the future of agentic commerce
  • Scale and extend existing AI-powered customer experience systems
  • Improve the multi-turn and multi-agent customer support system
  • Define scalable offline evaluation for complex multi-turn open-ended tasks
  • Research and prototype Human-In-The-Loop Reinforcement Learning to power an insights flywheel
  • Pioneer the architecture for customer-specific long-term memory
  • Extend the agentic system to support product recommendation, customer onboarding, risk diligence, activation, and upselling

Benefits

  • Medical insurance
  • Dental insurance
  • Vision insurance
  • 401(k)
  • Equity