About the Role
Abnormal Security is looking for an Engineering Manager to lead the Message Detection Decisioning team. At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. That’s what makes our novel behavioral-based approach so…Abnormal. Abnormal has constantly been named as one of the top cybersecurity startups and our behavioral AI system has helped us win various cybersecurity accolades resulting in being trusted to protect more than 8% of the Fortune 1000 (and ever growing).
In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Message Detection Decisioning team plays a central role, where it is responsible for building an extremely precise Detection Engine that can operate on hundreds of millions of messages at milliseconds latency. Every email ingested by Abnormal flows through the workflow owned by the Detection Decisioning team, which applies various signals and detectors on a message, computes the final decision for the system, and consequently chronicles attribution to drive various offline and online metrics.
The EM will report to the Senior EM of the Message Detection Team, and will lead a team that is primarily composed of backend engineers. The team builds both metadata / behavioral signals, and owns the decisioning pipeline which consumes the output of multiple heuristic/ML detectors and produces various decisions including the maliciousness, categorization, classification and attribution aspects of a message. The team also interfaces and collaborates with Machine Learning teams for ML Ops projects.
The Engineering Manager’s success or failure impacts our ability to build and iterate on a high precise detector engine, which is the core of our business and that makes the success of this team, and its leader, so massively impactful.
What you will do
- Own the execution success of the quarterly roadmap for the Detection Decisioning team; engage continuously with the Tech Leads to help adjust and prioritize current roadmap items according to the team’s charter and company priorities.
- Deliver on:
- Business criticality module to automatically maintain precision of the detection engine at both overall and individual customer levels.
- Standardizing and scaling the message decisioning systems as new heuristics and ML detectors are added to the system.
- Cost efficacy projects to help scale the detector decisioning infrastructure efficiently as the scale of customers and messages processed grow by 10-50x
- Own both directly customer impacting metrics and system metrics and able to work with the team to proactively identify and repair degradations:
- High Precision metrics for both onboarded and new customers
- Automation metrics for responses to customer specific requirements
- System metrics related to scaling of detectors including efficiency and health metrics
- Own the business logic layer for signal generation for both message metadata/content and current/historical user behavior, and systems and processes to continuously adapt and improve signals.
- Drive processes to enable the team to deliver on projects that are set by TLs as part of the technical roadmap.
- Manage the quarterly roadmap updates, project time estimates, weekly sprint planning, day-to-day standups
- Identify risks on project delivery (technical, operational, dependency risks) and escalate to appropriate technical leads
- Able to assess progress in a metrics-oriented manner
- Provide continuous feedback
- Responsible for mentoring and growing the engineers on the team by providing constructive feedback at regular intervals to help them successfully execute high impact projects.
- Drive Stakeholder alignment : Collaborate with the platform and infrastructure initiatives on company wide initiatives to help increase efficiency, customer adoption and engineer effectiveness goals.
- Drive stakeholder alignment: Proactively identify and collaborate with platform and infrastructure teams on company-wide initiatives including
Must Haves
- 1+ years experience of managing data driven product teams running at large scale data ( 100M+ ) and ability to guide a team technically in this respect.
- 4+ years of hands-on experience in engineering building and safely shipping backend heavy product features or ML adjacent systems at high velocity.
- Metrics driven culture: Has led a team of engineers in building out systems and displayed the ability to define metrics of excellence and setup processes to continuously monitor and maintain high standards on metrics.
- Be Customer obsessed: Worked with multiple stakeholders to gather requirements and then prioritize and balance against the team's roadmap.
- Set High standards - sets high standards and expectations for project execution for themselves and the whole team.
Nice to Have
- Familiarity with ML models, feature engineering knowledge, ML model work
- Familiarity with cyber security industry
- MS degree in Computer Science, Electrical Engineering or other related engineering field
- Experience with hiring and retention of top talent
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