Staff Software Engineer Platform & Infrastructure

About the Role

Enterprises of all sizes trust Abnormal Securitys cloud products to stop cybercrimeand these products are only as powerful as the platform they run on. The Platform Infrastructure team builds and operates the core systems that make Abnormals AI-driven detection and prevention possible: delivering reliability scalability and security at cloud scale.

Were looking for a Staff Software Engineer to lead foundational efforts across multiple areas of Platform this role youll guide a high-performing team shape the roadmap for a true self-service infrastructure platform and drive ambitious technical projects that use AI to automate and elevate how we build and operate our systems.

The ideal candidate:

• Tackles complex ambiguous problems and turns them into actionable plans.
• Leads by example and dives deep when needed.
• Embodies our VOICE values and builds software that delights customers.
• Earns trust across Engineering Product and Design through thoughtful collaboration.

Team mission: Build and evolve the core infrastructurecompute orchestration and data platformthat powers Abnormals AI/ML products at scale. We treat platforms as products: usable reliable secure and cost-efficient.

What you will do

• Shape the core areas of Platform Infrastructure such as compute (EC2/EKS autoscaling container runtime) and orchestration (Kubernetes workload APIs multi-cluster policy/quotas) as well as data platform (streaming batch durable storage data tooling)with demonstrated depth in at least two of these.
• Design and drive platform architecture & roadmap to support Abnormals expanding AI/ML portfolioscaling seamlessly across services tenants and regions.
• Partner deeply with product & ML workflows to make pragmatic trade-offs accelerating our shift to a platform-first operating model and enabling self-service.
• Raise the bar on operational excellence (SLOs availability performance incident response change management on-call hygiene) and help teams consistently meet it.
• Act as the teams technical lead: define quarterly roadmaps de-risk delivery mentor engineers and land high-leverage cross-team initiatives.
• Champion AI-native software development guiding teams on architecture data gravity feature stores model/service interfaces and evaluation pipelines.
• Own cost-conscious engineering optimizing design and operations to balance performance reliability and spend (capacity planning right-sizing caching storage tiers).
• Instill strong platform product practices: crisp APIs great docs clear SLAs/SLOs telemetry by default and paved paths that increase developer velocity.

Must haves

• Proven experience building and scaling data-intensive distributed backend systems in high-growth environments.
• 5 years as a Senior/Staff engineer building platforms tools or infrastructure that materially increase engineering velocity and reliability.
• A strong track record as a change agentreshaping infra strategy and shipping impactful self-service platform offerings in startup settings.
  
  
• Depth in at least two of the following three areas:

1. Compute (e.g. EC2 autoscaling container runtimes networking security hardening)
2. Orchestration (e.g. Kubernetes/EKS controllers/operators scheduling policies multi-cluster)
3. Data Platform (e.g. Kafka/Kinesis/SQS; Spark/Databricks/DBT/Airflow; S3; PostgreSQL/MySQL; DynamoDB/RocksDB/Redis/OpenSearch; data governance/quality/lineage)
   
   

Nice to haves

• Experience building multi-tenant or regulated (e.g. FedRAMP-like) platforms isolation boundaries and guardrails.
• Background with feature stores offline/online consistency model serving and evaluation/feedback loops.
• Prior leadership of cross-org migrations (e.g. to Kubernetes event-driven architectures or a unified data platform).

How we work

• Product mindset: platform as a product with clear APIs docs SLAs and adoption metrics.
• Automation first: paved paths and golden configs over bespoke snowflakes.
• Measured outcomes: reliability latency cost and developer experience over vanity metrics.

#LI-ML1

Required Experience:

Staff IC