Senior Software Engineer, Abnormal Security

Data Platform Team

$175.8-206k

AWS
GCP
Python
Kafka
Airflow
Azure
Spark
Golang
Senior level
Remote in US
Abnormal Security

Cloud email security platform

Job no longer available

Abnormal Security

Cloud email security platform

501-1000 employees

B2BArtificial IntelligenceSaaSCyber SecurityCloud ComputingFraud

Job no longer available

$175.8-206k

AWS
GCP
Python
Kafka
Airflow
Azure
Spark
Golang
Senior level
Remote in US

501-1000 employees

B2BArtificial IntelligenceSaaSCyber SecurityCloud ComputingFraud

Company mission

To make the cloud a safer place for businesses.

Role

Who you are

  • 5+ years of experience working on data-intensive applications and distributed systems
  • Strong programming skills in Python, Golang, or similar languages
  • Depth in at least one key area of the Data Platform tech stack - Relational DBs, key value and/or document datastores, caches, Kafka, Spark (or other batch processing systems)
  • Excellent ability and strong desire to onboard and mentor other engineers
  • Experience in working with AWS (or a similar public commercial cloud such as Azure / GCP)

Desirable

  • Prior experience in up-leveling the use of Airflow (or similar data orchestration systems) in a tech startup to support their growth and scale

What the job involves

  • The Data Platform team is looking to add a Senior Software Engineer
  • The individual in this role will have the opportunity to partner closely with our existing world class team of engineers as we define and build the next generation data platform
  • Scale and optimize our use of online datastores in critical services
  • Work cross functionally with R&D teams to identify scalability gaps in their data intensive systems, build and execute on plans to mitigate them
  • Define and deliver our data platform offerings across AWS, Azure to empower and delight our internal engineering customers
  • Optimize the performance of offline data processing systems (we use Spark / Databricks) to increase efficiency and cut costs

Our take

Fraud involving impersonation is one of the top causes of online financial crime. Criminal tactics like email account spoofing, where the criminal impersonates an official account to steal personal information or money, are rife. Abnormal Security is a startup aimed at handling these hyper-targeted and personalized email attacks by analyzing communications and identifying potential fraud before it can take place.

The fraud detection space is extremely competitive but Abnormal Security differentiates itself through its focus on the threat of impersonation rather than a spectrum of threats. This has allowed it to amass a wealth of data relating specifically to high-risk impersonation attacks, analyzing over 45,000 signals to detect any anomalies.

Its specialized approach has fueled rapid growth, leading to a $4B valuation after a Serice C Funding round. Now, Abnormal plans to double down on product development and expand internationally, prioritizing markets where data security laws necessitate a local presence. By staying focused on impersonation, Abnormal Security positions itself as a formidable force in the fight against online financial crime.

Freddie headshot

Freddie

Company Specialist

Insights

Top investors

Few candidates hear
back within 2 weeks

11% employee growth in 12 months

Company

Funding (last 2 of 4 rounds)

Aug 2024

$250m

SERIES D

May 2022

$210m

SERIES C

Total funding: $534m

Company benefits

  • Healthcare
  • Flexible PTO
  • 401k
  • One Medical
  • Flexible Spending Account
  • Mental Health Resources
  • Home Office Stipend
  • Monthly Internet & Phone Stipend
  • Health and Wellness Stipend

Company HQ

Yerba Buena, San Francisco, CA

Founders

Having started their career as a Software Engineer, co-founded GamerNook.com, Bloomspot, and Adstack before spending 3 years at Twitter. Co-founded Abnormal Security in April 2018, and has been CEO since.

Previously Senior Software Engineer at Twitter and Google. Was also Software Architect at TellApart.

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