Senior Software Engineer, AI-Native Platform (Remote)

ezCater, Inc•Boston, MA

2d•$158,000 - $190,000•Remote

About The Position

ezCater is hiring senior software engineers to build shared platform capabilities across administration, integrations, and transaction-heavy product experiences. This role is centered on backend services, APIs, workflow orchestration, and reliable distributed systems. We are looking for engineers who are fluent in an AI-native SDLC. That means more than familiarity with tools like Claude, Codex, or Cursor. The right engineer knows how to use AI effectively across planning, implementation, review, testing, and iteration, and understands how to improve the surrounding workflows, skills, and engineering standards. Go experience is strongly preferred. Deep experience in a similar backend language is also valuable.

Requirements

Strong software engineering experience building backend systems and APIs in production
Strong fluency with AI-assisted software delivery and clear judgment about where AI helps and where rigor matters most
A practical understanding of AI-native workflows, including structured context, iterative loops, and high-quality review and testing practices
Experience in Go, or deep proficiency in a comparable backend language such as Java
Experience building and operating transactional databases such as Postgres, RDS, or Aurora, including schema design, migrations, query performance, and reliability
Experience designing APIs, service boundaries, data models, and integration patterns in distributed systems
Comfort with workflow orchestration, event-driven architectures, and operational complexity
A strong quality mindset across testing, CI/CD, telemetry, and production ownership
Strong communication and a high-ownership approach to technical execution

Nice To Haves

Experience building shared platform capabilities used by multiple teams or products
Experience in fintech, payments, spend controls, ledgering, or other transaction-heavy systems
Experience with admin systems, integration platforms, or enterprise workflow products
Experience helping teams adopt more effective AI-assisted engineering practices

Responsibilities

Build shared services, APIs, and workflows that support administrative experiences, integrations, and core platform capabilities
Design reliable backend systems for cross-domain business flows and operationally critical use cases
Apply AI effectively throughout the software lifecycle, including implementation planning, coding, review, testing, and quality improvement
Contribute reusable engineering skills, patterns, and guidance that improve how teams work with AI
Partner with product, design, and engineering peers to turn ambiguous problems into well-scoped, high-quality deliveries
Own quality through testing, observability, safe rollout practices, and production issue investigation