Staff Software Engineer - Instant Access

About the Role

The goal of the Instant Access team is ambitious: to support every long-tail institution with Plaid, ensuring any issues are detected, triaged, and resolved automatically. This role will require close collaboration 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, the selected candidate will significantly influence technical direction and the evolution of a new capability, potentially changing how Plaid builds and operates software.

What You Will Do

• 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.

What We Are Looking For

• 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, with considerable time spent designing and building actual systems.
• Experience with applied AI systems and Large Language Models (LLMs) is preferred.
• Strong understanding of system design, architecture, and scalability.
• Ability to work in a fast-paced environment, making trade-offs between technical excellence and the rapid deployment of working systems.
• Excellent problem-solving skills, with the ability to approach complex problems from multiple angles.
• Strong communication and collaboration skills, with the ability to work closely with cross-functional teams.

Nice to Have

• Previous experience building production generative models or applied AI systems.
• Knowledge of financial institutions and their systems.
• Experience with cloud platforms (AWS, GCP, Azure).
• Familiarity with containerization (Docker) and orchestration (Kubernetes).

Benefits and Perks

• Competitive salary and equity package.
• Comprehensive health, dental, and vision insurance.
• Flexible PTO policy and generous parental leave.
• Access to cutting-edge technologies and tools.
• Professional development opportunities, including conference sponsorships and training programs.
• Remote work stipend and equipment budget.
• Collaborative and dynamic work environment with a team of experienced professionals.

• Ensure your resume highlights specific experience with backend and platform systems, as well as any work with applied AI systems or LLMs.
• Familiarize yourself with Plaid's technology stack and be prepared to discuss how you can contribute to their innovative approach to fintech.
• Practice explaining complex technical concepts in a clear, concise manner, as strong communication skills are essential for this role.
• Be prepared to provide examples of times when you had to balance divergent and convergent thinking in your work, and how you approached those challenges.
• Consider creating a personal project or contributing to open-source projects that demonstrate your skills in AI, LLMs, or backend development to stand out as a candidate.
• Review common system design interview questions and practice whiteboarding exercises to prepare for technical interviews.