Software Engineer I Federated Intelligence Platform

Enterprises of all sizes trust Abnormals AI-native security products to stop cybercrime and protect critical communications identities and infrastructure in the cloud. Our products are data- and systems-intensive operating at high scale and low latency across multiple clouds and regions.

As a Software Engineer I on the Federated Intelligence Platform (FIP) team: you will design and maintain high-volume ingestion and low-latency services across global infrastructures playing a vital role in upholding detection efficacy as the company expands its security footprint into identity and AI-agent protection. Youll learn how to design and implement production-quality systems work in an AI-native engineering environment and contribute to services that are reliable scalable and security-critical.

FIP serves as the federated intelligence layer within the Abnormal Data Platform managing the ingestion storage and retrieval of critical entity insights and threat indicators that drive core detection and the customer portal.

• Implement and ship well-scoped features and improvements in collaboration with more senior engineers from design review through implementation testing and rollout.
• Own smaller tasks and components end-to-end including clarifying requirements breaking work into steps writing code and validating changes in test and production environments with support from the team.
• Collaborate on the reliability and performance of existing systems by fixing bugs addressing simple bottlenecks and contributing to refactors that improve readability maintainability and correctness.
• Participate in operational work appropriate to your level such as helping debug issues improving runbooks and learning incident-handling practices before joining the formal on-call rotation.
• Work closely with partner teams and stakeholders (other engineering teams Detection/ML Product Infra/Platform) to understand how your changes interact with upstream and downstream systems.
• Use AI tools as part of your development loopfor code suggestions tests documentation and experimentswhile learning how to validate AI-generated output and maintain engineering-quality standards.
• Contribute to documentation and knowledge sharing by writing clear comments updating docs and runbooks and sharing learnings from projects code reviews and incidents.
• Invest in your growth by seeking feedback pairing with teammates and taking on progressively larger and more ambiguous work as you gain experience.

• 1 years of professional software engineering experience or equivalent experience from internships research or significant personal projects ideally in backend infrastructure full stack or other production-oriented systems.
• Solid programming skills in at least one modern language used at Abnormal (e.g. Python Go TypeScript/JavaScript or similar)
• Strong software engineering fundamentals: data structures basic algorithms writing clean and testable code debugging and working with version control (e.g. Git).
• Practical experience with relational or NoSQL storage solutions and schema design
• Competency in cloud infrastructure and container orchestration using AWS Docker or Kubernetes
• Foundational knowledge of high-scale event-driven architectures and message queuing
• Clear concise communication skills: you ask good questions can explain your thinking and collaborate well in a remote distributed team environment.
• A strong growth mindset and willingness to learnyou seek feedback own mistakes and are motivated to keep improving your craft and impact.

• Experience with distributed systems high-throughput pipelines or large-scale data stores (e.g. PostgreSQL DynamoDB Redis RocksDB Kafka Spark OpenSearch/Elasticsearch)
• Familiarity with Airflow or equivalent workflow orchestration and data pipeline management tools
• Background in production observability using Grafana or Prometheus and experience with on-call rotations
• Proficiency and comfort utilizing AI-augmented development workflows and engineering toolsets
• Background or coursework in security threat detection or large-scale messaging systems particularly systems processing significant volumes of data or requests.
• Exposure to containerization and orchestration (Docker Kubernetes) and infrastructure-as-code tooling.

• Youll solve hard meaningful problems at the intersection of AI security and large-scale distributed systems.
• Youll work with smart kind and ambitious teammates who care deeply about craftsmanship learning and helping each other grow.
• Youll get real ownership and autonomy over important parts of our systems and roadmap with clear opportunities to grow toward Senior and Staff roles over time.
• Youll be part of an AI-native R&D organization with strong investment in tools workflows and training to help engineers use AI to move faster while raising the quality bar.

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