Staff Software Engineer

Braze Braze · Enterprise · Toronto, ON · Engineering

Staff Fullstack Engineer to join the Core Objects team, driving architecture, scalability, and performance of a complex, high-scale backend system. The role involves extending the ingestion pipeline, optimizing performance and cost, and shaping core data structures. The team extensively integrates AI into its daily workflow, leveraging agentic tools to navigate a large Ruby monolith and create proof of concepts.

What you'd actually do

  1. conceive, design, and implement large-scale systems and services that handle massive data volumes and complex workloads in real time, including extending our high-scale ingestion pipeline to ingest new and advanced data objects
  2. take ownership of the complex backend systems behind Braze's core data objects, continuously improving their performance, reliability, and cost-effectiveness
  3. lead by example and mentor engineers on best practices in software design, coding, and operations
  4. work closely with other engineering teams, product managers, and stakeholders to ensure core data systems are effectively integrated and aligned with business objectives
  5. continuously identify opportunities to improve our systems, research new technologies, and advocate for their adoption where appropriate
  6. support and refine operational procedures (alerts, on-call rotation, troubleshooting playbooks) to maximize system stability and quality

Skills

Required

  • 7+ years of professional experience
  • hands-on work in full-stack development or back-end services
  • high-scale, high-throughput systems
  • building foundational data-driven systems at scale
  • architectural direction
  • scoping large efforts
  • managing technical debt
  • precise communication of complex technical concepts
  • driving major technical initiatives
  • software design
  • data structures
  • algorithms

Nice to have

  • Ruby
  • Ruby on Rails
  • React
  • Go
  • SQL/NoSQL databases
  • MongoDB
  • Snowflake
  • data lake solutions
  • Kubernetes
  • AWS
  • GCP
  • Azure
  • API design
  • monitoring
  • best practices
  • customer experience

What the JD emphasized

  • extensive integrations
  • agentic tools
  • large Ruby monolith
  • AI has been used across all stages of product delivery
  • 7+ years of professional experience
  • high-scale, high-throughput systems
  • building foundational data-driven systems at scale
  • distributed systems

Other signals

  • integrates AI into its daily workflow
  • leveraging agentic tools
  • AI has been used across all stages of product delivery
  • enhancing the team’s ability to deliver high-quality results more efficiently