Abnormal AI is on a mission to protect enterprises against email attacks with their innovative behavioral-based approach to Email Security. As a Software Engineer II, you will build and manage the infrastructure for their inbound email security product, ensuring it is scalable and resilient while collaborating with cross-functional teams.
Responsibilities:
- Standardize overall message detection flow and decisioning logic and allow our infrastructure to scale with an increasing number of customers, messages, signals, and detectors
- Build tooling and infrastructure that will enable engineers to push changes confidently and safely
- Develop tools and mechanisms that provide insight into detection efficacy and generate actionable steps to maintain high performance
- Guarantee seamless integration with other Abnormal products (e.g., Abuse Mailbox), and present detection outputs through a standardized interface for use by other Abnormal solutions
- Write code with testability, readability, edge cases, and errors in mind biasing towards simple iterative solutions
- Write and review technical design documents
- Participate in Sprint planning, code reviews, standups, and other aspects of the software development life cycle
Requirements:
- 2+ years experience designing and building software applications
- Experience with large scale systems with an emphasis on data intensive applications that require high availability, throughput, and low latency
- Experience with SQL and NoSQL databases such as PostgreSQL, DynamoDB, Redis, etc…
- Experience debugging using log analytic tools, metrics, and other signals
- Proven experience translating business requirements into software requirements and delivering high quality implementations
- Strong ability to independently solve complex problems
- Ability to work effectively with cross-functional teams
- BS degree in Computer Science, Software Engineering, Information Systems or other related engineering field
- Experience with Go and Python
- Experience in the cybersecurity industry, financial fraud, application security, or related industries
- Experience with big data, statistics, and Machine Learning
- Experience with Airflow, Kubernetes, Kafka, Spark, Pandas
- Experience with algorithms and optimization