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Abnormal AI protects organizations from cyber threats across email, identity, collaboration, and cloud applications. The Abnormal Data Platform (ADP) provides the data foundations powering detection and customer-facing products. Within ADP, the DIP Ingestion team builds integrations and runtime systems that bring data from these platforms into Abnormal's infrastructure.
You will build and operate backend services and ingestion pipelines at scale. You'll own complex features from product need through design, implementation, launch, and production support. Your work may span new source integrations, improvements to the ingestion framework, snapshot ingestion, and the reliability and freshness of data flowing to downstream teams. You'll grow your technical judgment while working closely with experienced engineers and product partners.
Key responsibilities:
- Build and improve secure, scalable integrations that collect data from third-party APIs and deliver it reliably to downstream systems.
- Own complex, well-scoped features end to end: clarify requirements, propose an approach, break work into milestones, implement, test, roll out, and measure outcomes.
- Contribute to ingestion-platform capabilities such as reusable connector patterns, self-serve integration workflows, and snapshot and event-ingestion paths.
- Use AI-assisted tools to accelerate integration development, testing, and troubleshooting while validating output and maintaining ownership of production quality.
- Improve ingestion freshness, correctness, and reliability by defining and tracking service-level goals, strengthening error handling and alerts, and investigating data gaps or delays.
- Diagnose issues across vendor APIs, ingestion services, and downstream interfaces; participate in on-call rotation and turn recurring failures into durable fixes.
- Collaborate asynchronously with engineers and partners across product and platform teams. Participate in design discussions and code reviews, and document the systems you change.
Requirements:
- 3+ years of software engineering experience, including hands-on development of production backend services in Python.
- Experience owning the delivery of complex features: turning a clearly defined problem into a technical approach, implementation, and successful launch.
- Strong fundamentals in backend design, APIs, data modeling, testing, debugging, and performance.
- Experience operating services in production and using logs, metrics, and alerts to investigate and resolve issues.
- Familiarity with cloud services and deployment practices, ideally AWS.
- Clear written communication and the ability to clarify ambiguous requirements with teammates and stakeholders across functions and time zones.
- Care for correctness, code quality, and the customer impact of data reliability.
Nice to have:
- Experience with Go, Kafka or another messaging system, and distributed data pipelines.
- Experience integrating with third-party SaaS APIs, including authentication, pagination, rate limits, and inconsistent source data.
- Familiarity with Docker or other container technologies and SQL databases.
- Experience with batch or snapshot ingestion, workflow orchestration, or configuration-driven integration frameworks.
