Senior / Staff Software Engineer - Backend (Grader)

New

JobgetherAI restaurant intelligence

CanadaFull-TimeStaff

SalaryCompetitive annual base salary ranging from USD 240,000 to USD 250,000

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Job Details

Experience: 7+ years of professional experience in backend engineering, platform engineering, or software development
Required Skills: Node.jsPostgreSQLMongoDBTypeScriptMicroservicesDistributed Systems

Have 7+ years of professional experience in backend engineering, platform engineering, or software development.
Demonstrate a track record of delivering production systems and owning and scaling mission-critical backend systems used by external customers.
Bring experience in product-driven technology companies, particularly B2C or B2B2C environments.
Be proficient in Node.js and TypeScript, or equivalent backend programming languages.
Have experience with relational and/or NoSQL databases, particularly PostgreSQL, MongoDB, or similar technologies.
Understand distributed systems, asynchronous processing, event-driven architectures, and large-scale data pipelines.
Have improved production system performance, reliability, observability, and scalability.
Have experience building customer-facing backend services in high-availability environments.
Be able to lead architectural redesigns, system migrations, or large-scale infrastructure improvements.
Bring strong software engineering fundamentals in system design, API development, database optimization, and service architecture.
Have problem-solving and analytical skills for making technical decisions in complex environments.
Work effectively across product, engineering, and operational teams.

Own the backend architecture and technical direction of Grader.
Design, develop, and maintain data pipelines that ingest, process, and enrich third-party information and AI-generated signals.
Build and operate reliable backend services for real-time restaurant scoring and customer-facing product experiences.
Optimize latency, availability, throughput, scalability, and production reliability.
Design and maintain event-driven architectures, asynchronous processing systems, and distributed workflows.
Establish and improve production observability, monitoring, alerting, and incident management.
Lead monolith decomposition and the transition toward scalable microservices.
Partner with product managers, AI specialists, and engineering teams to launch AI-powered scoring capabilities.
Own production systems from technical design and implementation through deployment, monitoring, and continuous improvement.

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