Staff Software Engineer, Plaid

• 8+ years of strong software engineering experience with a deep focus on backend and/or platform systems
• Ability to balance divergent thinking (exploring possibilities) with convergent thinking (evaluating feasibility)
• Must be comfortable working hands-on directly in the codebase. This is a builder archetype position. You will spend considerable time designing and then building the actual systems you own
• Must be comfortable moving fast, which means making trade-offs between technical excellence and the rapid deployment of working systems to validate whether approaches are fruitful

Desirable

• As a Staff Software Engineer on Instant Access, you'll set technical foundations for autonomous systems that operate directly in production
• You'll work across AI and product engineering to solve ambiguous, high-impact problems, while designing systems that can reason about failures, generate solutions, and safely take action at scale
• This is a hands-on role that combines deep technical leadership with implementation
• You'll partner closely with engineers, product managers, and leaders across NEA to identify opportunities for automation, define long-term architecture, and build the foundational systems that future AI initiatives will rely on
• As an early engineer on the team, you'll significantly influence technical direction and the evolution of a new capability. This could fundamentally change how Plaid builds and operates software
• Define the technical direction and architecture for autonomous AI systems that create, repair, and improve financial institution integrations
• Create novel observability, monitoring, and debugging platforms to provide engineers with deep visibility into the behavior, decisions, and performance of AI-powered systems
• Build LLM-powered code generation pipelines that write, validate, and ship production code end-to-end with minimal human intervention
• Design evaluation frameworks that measure correctness, reliability, and safety for non-deterministic systems operating at scale
• Architect self-healing infrastructure that detects, diagnoses, and repairs itself in under 24 hours
• Develop multi-layer safety architectures to ensure AI systems take the correct actions in production and degrade safely when uncertainty exists
• Partner closely with engineering and product leaders to identify high-leverage automation opportunities and turn them into production systems
• Raise the technical bar across the organization through mentorship, design reviews, and hands-on leadership