Senior Software Engineer, AI Internal Tools

Plaid; New York (NY); On-site; USD 190,800 - 262,800; Full time

Job summary

Plaid is seeking a Senior Software Engineer to build and operate internal systems that empower non‑engineering teams to automate workflows with AI. You will own the product and platform layer for internal tools, including auth, runtime, and deployment constraints to keep tools safe and maintainable.

You will define the right AI surface for non‑engineering users, ship early durable versions, and collaborate with internal users to ensure solutions address real problems.

Qualifications

• 5+ years of professional software engineering experience.
• Strong experience building and operating production systems.
• Experience building internal tools, platforms, or workflow software.
• Strong product judgment and communication in ambiguous spaces.
• Hands‑on experience using AI‑powered development tools, agents, or automation.
• Strong builder mindset; capable of creating first version of a product surface.

Responsibilities

• Design, build, and operate internal tools and platform capabilities for high‑leverage non‑engineering workflows.
• Translate ambiguous internal pain points into simple, durable software products.
• Define platform constraints for auth, runtime, storage, deployment, and maintenance for safety and scalability.
• Build with product judgment, balancing flexibility with defined boundaries between tools.
• Partner with Security, Infrastructure, and internal teams to ship reliable production systems.
• Own end‑to‑end systems, including implementation, rollout, support, and iteration.

Skills

5+ years software engineering

Production systems

Internal tools

AI-powered development

Product judgment

Ambiguity handling

Tools

Auth systems

Internal security

AI tooling

Job description

Plaid is seeking a Senior Software Engineer to build and operate internal systems that empower non‑engineering teams to automate workflows with AI. You will own the product and platform layer for internal tools, including auth, runtime, and deployment constraints to keep tools safe and maintainable.

You will define the right AI surface for non‑engineering users, ship early durable versions, and collaborate with internal users to ensure solutions address real problems.