Engineering Manager, AI Platform Integration
Plaid
Software Engineering, Other Engineering, Data Science
New York, NY, USA
Posted on Aug 1, 2025
The Access team owns the systems responsible for expanding and maintaining integrations with thousands of financial institutions—particularly long-tail institutions—by developing applied AI infrastructure to automate the traditionally manual workflows of integration creation and maintenance. We aim to change the cost curve of integrating with financial institutions, ensuring maximum institutional coverage with minimal manual effort, and delivering on Plaid's mission of financial access for all.
Our AI‑driven systems repair broken connections and accelerate the creation of new integrations using human‑in‑the‑loop workflows. This applied AI approach has already shown promise in increasing conversion, reducing latency, and other metrics that customers deeply care about
Responsibilities
- Lead the Access team as we scale applied AI tools from prototype to production.
- Ensure technical execution quality, delivery velocity, and team health.
- Partner cross-functionally with Product, MLE, and the Partnerships team to align on the roadmap and unblock integration bottlenecks.
- Evolve team processes and infrastructure to support rapid iteration without sacrificing reliability.
- Grow and mentor a high-performing engineering team.
- Actively participate in roadmap planning, design reviews, and hands-on technical work when needed.
- Drive accountability for longtail access uptime, reliability, and system observability.
Qualifications
- Demonstrated experience leading high-performing engineering teams.
- Strong product intuition and the ability to work across ambiguous problem spaces.
- Track record of mentoring engineers and growing technical leaders.
- Strong systems thinking and ability to evaluate architectural tradeoffs.
- Excellent communication and cross-functional collaboration skills.
Nice to Have
- Experience working with browser automation technologies.
- Familiarity with headless browsing frameworks.
- Previous work in fintech, integrations, or platform infrastructure.
- Hands-on experience building and deploying applied.
- AI-powered automation systems or a rudimentary applied ML experience.