Engineering Manager, AI Applications

Responsibilities

• Lead a team of 4 engineers (junior to staff level) through goal setting, coaching, and feedback
• Define and drive long-term strategy and manage execution in partnership with technical and product leaders
• Lead projects enabling and scaling business with largest AI customers and partners, starting with personal finance use cases
• Develop and evolve preferred integration patterns for Plaid with AI providers (API adaptations, official Plaid MCP Servers)
• Redefine how Plaid's consumer link experience embeds into conversational interfaces
• Architect the trust layer for agentic commerce
• Scale and extend AI-powered customer experience systems
• Improve homegrown customer support agent with multi-turn and multi-agent systems
• Define scalable offline evaluation for complex multi-turn open-ended tasks
• Research and prototype Human-In-The-Loop Reinforcement Learning (RLHF) for insights flywheel
• Pioneer architecture for customer-specific long-term memory
• Extend agentic systems to support customer journey areas: product recommendation, onboarding, risk diligence, activation, assistance, upselling, cross-selling

Requirements

• 8+ years of industry experience including time as a Staff-level engineer before transitioning to management
• 1+ years of engineering management experience
• Hands-on experience working with LLMs to build and ship products with real user feedback, including:
  • Prompt engineering
  • Fine-tuning
  • Retrieval augmented generation (RAG)
  • Semantic search (vector databases, embedding models)
  • Agent orchestration frameworks
  • Evaluation and monitoring frameworks for 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
• Track record of building and growing high-performing engineering teams
• Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility)
• Extremely curious and passionate about GenAI applications

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