Abnormal Security
Staff Software Engineer - Platform & Infrastructure
Abnormal Security, Myrtle Point, Oregon, United States, 97458
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 Infrastructure. In 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 agent reshaping infra strategy and shipping impactful,
self-service platform
offerings in startup settings. Depth in at least two of the following three areas: Compute
(e.g., EC2, autoscaling, container runtimes, networking, security hardening) Orchestration
(e.g., Kubernetes/EKS, controllers/operators, scheduling, policies, multi-cluster) Data Platform
(e.g., Kafka/Kinesis/SQS; Spark/Databricks/DBT/Airflow; S3; PostgreSQL/MySQL; DynamoDB/RocksDB/Redis/OpenSearch; data governance/quality/lineage) Hands-on with our stack
(or equivalent): Python, Golang, Terraform/Terragrunt, PostgreSQL, Kafka, Redis, OpenSearch, AWS, Kubernetes. Strong IaC, observability, and SRE fundamentals (SLOs, error budgets, incident management, postmortems, capacity planning). 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 At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $209,800 $246,800 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here. #J-18808-Ljbffr
Staff Software Engineer
to lead foundational efforts across multiple areas of Platform Infrastructure. In 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 agent reshaping infra strategy and shipping impactful,
self-service platform
offerings in startup settings. Depth in at least two of the following three areas: Compute
(e.g., EC2, autoscaling, container runtimes, networking, security hardening) Orchestration
(e.g., Kubernetes/EKS, controllers/operators, scheduling, policies, multi-cluster) Data Platform
(e.g., Kafka/Kinesis/SQS; Spark/Databricks/DBT/Airflow; S3; PostgreSQL/MySQL; DynamoDB/RocksDB/Redis/OpenSearch; data governance/quality/lineage) Hands-on with our stack
(or equivalent): Python, Golang, Terraform/Terragrunt, PostgreSQL, Kafka, Redis, OpenSearch, AWS, Kubernetes. Strong IaC, observability, and SRE fundamentals (SLOs, error budgets, incident management, postmortems, capacity planning). 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 At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $209,800 $246,800 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here. #J-18808-Ljbffr