Senior Software Engineer II, Decisioning Studio Integrations Team

Braze•Austin, TX

15h•Hybrid

About The Position

Braze is hiring a Senior Software Engineer II for the Decisioning Studio Integrations team, which builds BrazeAI Decisioning Studio, a reinforcement-learning platform that continuously experiments to personalize customer engagement. The team is responsible for ingesting enterprise customer data at very large scale from warehouses, engagement platforms, and other systems, and delivering recommendations across channels including email, SMS, push, and in-app messaging. The engineer will lead complex integration projects from design through rollout and set technical direction for the integration platform. The role involves building data-ingestion and activation integrations, designing reliable pipelines that handle varied data formats and failures, and accounting for multi-region deployment, data residency, and personally identifiable information. The position also includes production ownership, Datadog instrumentation, participation in an on-call rotation, collaboration with data scientists, ML engineers, and product managers, and mentoring other engineers. The role offers a hybrid way of working. For candidates based in the United States, the stated starting base pay range is $156,364–$279,957 per year, with expected on-target earnings of $172,000–$306,000 per year, including bonus or commission. The role also qualifies for equity grants in restricted stock units. Compensation varies based on individualized factors such as market location, job-related knowledge, skills, and experience.

Requirements

At least 6 years of backend engineering experience building and operating distributed systems in production.
Technical leadership experience 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.
Strong grasp of event-driven architecture and reliability patterns, including 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 and Kubernetes; GCP is preferred.
Experience with AI coding assistants and sound judgment about when to use them.
Clear communication and ability to work well with engineering, data science, and product teams.
Self-starter who identifies problems and works around obstacles without waiting for direction.

Nice To Haves

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.

Responsibilities

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 data ingestion and activation orchestration.
Build ingestion pipelines for batch pulls, file drops, APIs, and streaming, accepting arbitrary schemas while preventing bad data from reaching models.
Build event-driven, fault-tolerant activation pipelines that deliver recommendations on schedule, recover from partial failures, and prevent duplicate sends.
Design for multi-region deployment and compliance requirements, including data residency and PII handling.
Own systems in production, instrument them with Datadog, participate in the on-call rotation, and investigate incidents through to root cause.
Work with data scientists, ML engineers, and product managers to turn integration requirements into reusable platform capabilities.
Mentor engineers and raise standards for code quality, testing, and design review.

Benefits

Competitive compensation that may include equity.
Retirement and Employee Stock Purchase Plans.
Flexible paid time off.
Medical, dental, vision, life, and disability benefit plans.
Fertility benefits and equal paid parental leave.
Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend.
Curated in-office employee experience designed to foster community, team connections, and innovation.
Opportunities to give back, including an annual company-wide Volunteer Week and donation matching.
Employee Resource Groups.
Hybrid ways of working.