Software Engineer II - ADEX
Abnormal Security3 days ago
Bengaluru, IndiaMid Level
H1B Sponsor
Responsibilities
- Design, build, launch, monitor, operate, and continuously improve production detection systems.
- Own detection projects through ambiguity by defining scope, risks, milestones, tradeoffs, and delivery plans.
- Analyze missed attacks and translate attack patterns into detection enhancements and new detection systems.
- Write and tune detection logic, add scored signals and attributes across pipelines, and minimize false positives.
- Build and evaluate LLM-based detection agents using rigorous precision and recall measurement.
- Expose detections as reusable intelligence for other products and teams.
- Participate in on-call rotations, resolve customer escalations, and improve observability and runbooks.
- Use AI-assisted development for code, tests, data analysis, experiments, and documentation while validating results.
- Document work, share learnings, and contribute to code and design reviews.
Requirements
- 3+ years of professional software engineering experience shipping and operating production systems.
- Strong fundamentals in data structures, algorithms, system design, testing, debugging, and maintainable code.
- Strong Python proficiency and ability to learn new languages and frameworks.
- Comfort with SQL and analyzing large datasets to identify meaningful signals.
- Detection or adversarial mindset with interest in attack analysis and bypass strategies.
- Experience using AI coding agents and enthusiasm for building LLM-powered detection systems.
- Ability to scope ambiguous projects, make tradeoffs, deliver reliably, and communicate status clearly.
- Excellent written and verbal communication skills, particularly in distributed teams.
- Experience with distributed systems, high-throughput pipelines, or large-scale data stores is preferred.
- Background in security, threat detection, anti-abuse, fraud detection, or trust and safety is preferred.
- Experience with ML or LLM evaluation, including precision/recall tradeoffs, evaluation harnesses, or prompt iteration, is preferred.
- Familiarity with domain and DNS concepts, identity and impersonation signals, large-scale data tooling, containerization, orchestration, infrastructure as code, frontend frameworks, or ML/ML Ops is preferred.
- Startup experience balancing speed, quality, and ambiguity is preferred.
Tech Stack
Amazon DynamoDBApache AirflowApache KafkaApache SparkDatabricksDockerElasticsearchKubernetesPostgreSQLPythonReactRedisSQL
Categories
About Abnormal Security
Abnormal AI is the leading AI-native human behavior security platform, leveraging machine learning to stop sophisticated inbound attacks and detect compromised accounts across email and connected applications.