Senior Software Engineer II, Decisioning Studio Integrations Team

We're looking for a Senior Software Engineer II to join the Decisioning Studio Integrations team building BrazeAI Decisioning Studio™. Decisioning Studio is a reinforcement learning platform that runs continuous experiments to personalize customer engagement for each individual. Its results depend on the data it learns from and on the channels that carry its decisions to customers. Our team owns both. We ingest enterprise customer data of any schema and at a very large scale from warehouses, engagement platforms and other enterprise systems. We also deliver the recommendations from our RL pipelines across email, SMS, push, in-app and other channels. These are high-impact, customer-facing features.

In this role, you will:

• Lead complex integration projects from design through build and rollout, and set technical direction for the Decisioning Studio integration platform
• Design and build integrations with cloud data warehouses, customer engagement platforms and other enterprise systems, for both data ingestion and activation orchestration
• Build ingestion pipelines that handle every way customers send data, including batch pulls, file drops, APIs and streaming, and accept arbitrary schemas without letting bad data reach our models
• Build event-driven, fault-tolerant activation pipelines that deliver recommendations on schedule, recover cleanly from partial failures and never send twice
• Design for multi-region deployment and compliance requirements, including data residency and PII handling
• Own your systems in production. Instrument them with Datadog, take part in the on-call rotation, and take incidents all the way to the root cause
• Work with data scientists, ML engineers and product managers to turn integration requirements into reusable platform capabilities
• Mentor engineers and raise the bar for code quality, testing and design review
• 6+ years of backend engineering experience building and operating distributed systems in production
• A track record of technical leadership: owning complex projects end to end, making architecture decisions and setting direction for other engineers
• Experience building data pipelines or integrations that move very large volumes of data between systems, including schema changes, backfills and partial failures
• A strong grasp of event-driven architecture and reliability patterns: message brokers such as Kafka, idempotency, retries with backoff, dead-letter handling, and at-least-once versus exactly-once tradeoffs
• Proficiency in Python and SQL
• Hands-on experience with cloud infrastructure (GCP preferred) and Kubernetes
• Experience with AI coding assistants, and the judgment to know when they help and when they don't
• A clear communicator who works well with engineering, data science and product
• A self-starter who finds problems and works around obstacles without waiting for direction
• Experience integrating with cloud data warehouses such as BigQuery, Snowflake or Redshift
• Experience integrating with customer engagement platforms such as Braze, Adobe, Salesforce Marketing Cloud or Klaviyo
• Experience building multi-region systems under data residency and compliance requirements
• Experience running ML systems in production

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