Braze - AI Platform Engineer II
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Requirements
• 2-4 years of experience in platform engineering, infrastructure, or a related backend role • Solid understanding of platform architecture, particularly in ML or data-intensive environments • Hands-on experience with Kubernetes and cloud infrastructure (GCP preferred) • Ability to troubleshoot complex distributed systems under pressure • Writes clean, modular code with a focus on testable APIs and maintainable design • Experience working with AI coding assistants. Understands effective prompting strategies and can articulate when these tools add value versus when they're not appropriate • Clear communicator who can work across technical and non-technical stakeholders • Proactive problem solver who identifies issues and works around obstacles without waiting for direction • For candidates based in Ontario, the pay range for this position at the start of employment is expected to be between CA$125,280 and CA$235,736/year with an expected On Target Earnings (OTE) between CA$139,200 and CA$258,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that all Braze employees own a piece of our company.
Responsibilities
• Build and maintain critical services and subsystems on our AI platform, balancing performance with cost-effective operations • Implement cloud-native solutions that ensure reliability, scalability, and fault tolerance • Troubleshoot production incidents end-to-end, going deep to identify root causes and implement durable fixes • Contribute to observability practices using Sentry and Datadog to proactively detect issues and minimize downtime • Collaborate with data scientists, ML engineers, and product teams to translate real-world use cases into platform capabilities • Improve developer experience by streamlining workflows, enhancing tooling, and supporting MLOps best practices • Core Data & ML: Python, Ibis, FastAPI, Dataproc (Spark), SQL, BigQuery, MLflow, Streamlit • Platform & Infrastructure: Google Cloud Platform, AWS, Kubernetes, Helm, Terraform • Workflows & Orchestration: Airflow, RabbitMQ, Celery • CI/CD: GitHub Actions, Jenkins • Observability: Sentry, Datadog • Production ML at scale: no toy datasets or notebook demos; you’re building infrastructure that powers real AI workloads • Engineering rigor: unit and integration tests, modular design, CI/CD, pair programming, and code reviews are how we work, not aspirations • Learn continuously: deep exposure to ML system architecture, end-to-end ML workflows, and reinforcement learning systems
Benefits
• Braze benefits vary by location, and we encourage you to review our specific benefits offerings for each country here. More details on benefits plans will be provided if you receive an offer of employment. • From offering comprehensive benefits to fostering hybrid ways of working, we’ve got you covered so you can prioritize work-life harmony. Braze offers benefits such as: • Retirement and Employee Stock Purchase Plans • Flexible paid time off • Comprehensive benefit plans covering medical, dental, vision, life, and disability • Family services that include fertility benefits and equal paid parental leave • Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend • A curated in-office employee experience, designed to foster community, team connections, and innovation • Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching • Employee Resource Groups that provide supportive communities within Braze • Collaborative, transparent, and fun culture recognized as a Great Place to Work®
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