Senior Software Engineer II, Decisioning Studio Integrations Team

Description

The company runs a customer engagement platform for brands, covering cross-channel messaging, journey orchestration and AI-driven decisioning for one-to-one personalization.

This role sits on the integrations team for the company's reinforcement learning product, which runs continuous experiments to personalize engagement for each person. Its results depend on the data it learns from and on the channels that carry its decisions, and the team owns both.

The team ingests enterprise customer data of any schema, at very large scale, from warehouses, engagement platforms and other enterprise systems. It then sends model recommendations out through email, SMS, push, in-app and other channels. These are high-impact features that customers use directly.

The company is headquartered in New York, with offices in Austin, Berlin, Bucharest, Chicago, Dubai, Jakarta, London, Paris, San Francisco, São Paulo, Singapore, Seoul, Sydney and Tokyo.

Success here means setting a high bar for yourself and others, acting with autonomy, taking accountability and staying open to other views.

Some candidates hold back from applying unless they meet 100% of the criteria. If that is you, apply anyway, since the company would like to meet you.

Responsibilities

• Lead complex integration projects from design through build and rollout, and set technical direction for the integration platform.
• Design and build integrations with cloud data warehouses, engagement platforms and other enterprise systems, covering both data ingestion and activation orchestration.
• Build ingestion pipelines for batch pulls, file drops, APIs and streaming, accepting arbitrary schemas while keeping bad data away from the models.
• Build event-driven, fault-tolerant activation pipelines that deliver recommendations on schedule, recover cleanly from partial failures and never send a message twice.
• Design for multi-region deployment and compliance, including data residency and PII handling.
• Own your systems in production: instrument them with Datadog, join the on-call rotation and follow incidents through to root cause.
• Work with data scientists, ML engineers and product managers to turn integration needs into reusable platform capabilities.
• Mentor engineers and raise the standard for code quality, testing and design review.

Requirements

• 6+ years of backend engineering experience building and running distributed systems in production.
• A record of technical leadership: owning complex projects end to end, making architecture decisions and directing other engineers.
• Experience building pipelines or integrations that move very large data volumes, including handling schema changes, backfills and partial failures.
• A solid grasp of event-driven architecture and reliability: 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 cloud infrastructure experience and Kubernetes. GCP is preferred.
• Experience with AI coding assistants, and the judgment to know when they help and when they do not.
• A clear communicator who works well with engineering, data science and product.
• A self-starter who spots problems and works around obstacles without waiting for direction.
• Bonus: experience integrating with cloud data warehouses such as BigQuery, Snowflake or Redshift.
• Bonus: experience integrating with customer engagement platforms such as Adobe, Salesforce Marketing Cloud, Klaviyo or the company's own platform.
• Bonus: experience building multi-region systems under data residency and compliance requirements.
• Bonus: experience running ML systems in production.

Conditions

This is a hybrid role.

For candidates based in Canada, the expected pay range at the start of employment is CA$186,838 to CA$334,740 per year, with expected On Target Earnings of CA$205,600 to CA$366,000 per year, including bonus or commission. The exact offer may vary with market location, job-related knowledge, skills and experience.

The company is an equal opportunity employer and aims for equitable growth and opportunity inside and outside the organization.

Applications are screened partly with AI tools, which may amount to solely automated decision-making, and recruiters remain responsible for all hiring decisions. You may opt out of AI-assisted review and have other rights under the company's AI use; the talent team can answer questions. Bias audit summaries for these tools are published.

Benefits

• Benefits vary by location, and the company will share the specific plans for your country if you receive an offer.
• Competitive pay that may include equity.
• Restricted stock units as part of the total rewards package for the Canada role, so you own a share of the company.
• Retirement and employee stock purchase plans.
• Flexible paid time off.
• Medical, dental, vision, life and disability coverage.
• Fertility benefits and equal paid parental leave.
• Career pathing, learning platforms and a yearly learning stipend.
• An in-office experience designed to build community, team connections and innovation.
• An annual company-wide Volunteer Week and donation matching.
• Employee Resource Groups.
• Recognized as a Great Place to Work.