Senior Software Engineer II, Decisioning Studio Integrations Team

Description

The company runs a customer engagement platform that uses AI-driven decisioning, and it is growing quickly across the globe.

This is a Senior Software Engineer II role on the integrations team, which builds the connections that feed the platform's reinforcement learning models with customer data and deliver their recommendations to customers.

The platform's results depend on the data it learns from and on the channels that carry its decisions, and the team owns both.

The work covers email, SMS, push, in-app and other channels, and it is customer-facing and high-impact.

Responsibilities

• Lead complex integration work from design through build and rollout, and set the technical direction for the integration platform.
• Design and build connections to cloud data warehouses, engagement platforms and other enterprise systems, for both data intake and activation.
• Build ingestion pipelines that take in batch pulls, file drops, APIs and streams, accept any schema, and keep bad data away from the models.
• Create activation pipelines that are event-driven and fault-tolerant, shipping recommendations on time, recovering from partial failures and never sending a duplicate.
• Plan multi-region deployments that meet compliance rules, including data residency and PII handling.
• Run your systems in production with Datadog, join the on-call rotation, and follow incidents to the root cause.
• Partner with data scientists, ML engineers and product managers to turn integration needs into reusable platform features.
• Coach engineers and raise the standard for code quality, testing and design review.

Requirements

• 6+ years of backend engineering experience running distributed systems in production.
• Proven technical leadership: you have owned complex projects end to end, made architecture decisions and set direction for other engineers.
• Hands-on experience building pipelines or integrations that move very large data volumes, including schema changes, backfills and partial failures.
• Solid grasp of event-driven design and reliability patterns, including Kafka or similar brokers, 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, with GCP preferred, and Kubernetes.
• Experience with AI coding assistants, and the judgment to tell when they help and when they do not.
• Clear communication with engineering, data science and product teams.
• A self-starter who spots problems and works around blockers without waiting to be told what to do.
• Bonus points:
• Bonus: experience integrating with cloud data warehouses such as BigQuery, Snowflake or Redshift.
• Bonus: experience integrating with customer engagement platforms such as the company, Adobe, Salesforce Marketing Cloud or Klaviyo.
• Bonus: experience building multi-region systems under data residency and compliance requirements.
• Bonus: experience running ML systems in production.

Conditions

Hybrid work model.

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.

For candidates based in the United States, the expected starting pay is $156,364 to $279,957 per year, with expected On Target Earnings (OTE) of $172,000 to $306,000 per year including bonus or commission.

Final offers may vary based on factors such as market location, job knowledge, skills and experience.

The company is an equal opportunity employer that works to create equitable growth and opportunity.

You are encouraged to apply even if you do not meet 100% of the criteria.

AI tools screen applications and support scheduling and interview notes, with recruiters making all hiring decisions; screening may amount to solely automated decision-making, and you may have rights to opt out or request review, with bias audit summaries available.

Benefits

• Benefits vary by location, and details are shared with any offer.
• A comprehensive Total Rewards package that includes restricted stock unit (RSU) equity grants.
• Retirement savings and an Employee Stock Purchase Plan.
• Flexible paid time off.
• Medical, dental, vision, life and disability coverage.
• Fertility benefits and equal paid parental leave.
• Formal career pathing, learning platforms and a yearly learning stipend.
• A curated in-office experience designed to build community, team connections and new ideas.
• An annual company-wide Volunteer Week and donation matching.
• Employee Resource Groups.
• Recognized as a Great Place to Work.