Senior Software Engineer II, Decisioning Studio Integrations Team
WHAT YOU'LL DO
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
WHO YOU ARE
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
Bonus points:
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
For candidates based in the United States, the pay range for this position at the start of employment is expected to be between $156,364 and $279,957/year, with an expected On Target Earnings (OTE) between $172,000 and $306,000/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, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.
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