Senior Python Engineer — Data & Detection

About iVerify

We are Experts in Mobile Threat Hunting. The first mobile threat hunting company to protect mobile devices like any other vulnerable corporate endpoint.

The mobile security market has a problem. Simply put, current solutions fail to meet the sophistication of modern threats or the growing privacy desires of mobile device users. We believe that it is time for something new. Not only because we care deeply about the safety of frontline users like journalists and activists - many of whom are doing important and often dangerous work - but because enterprises and consumers deserve real protection from advanced mobile threats without sacrificing privacy.

We are building the first mobile threat hunting company to harmonize security and privacy in the face of a new class of mobile threats. Supported by some of the most well-respected VC firms, we aim to become the go-to mobile security solution for individuals who want to know they can trust their devices with their most sensitive information – without sacrificing privacy.

About the Role

We are seeking a Senior Python Engineer to join the team that builds the data backbone of our mobile EDR platform. You'll build the systems that ingest data at scale from mobile endpoints, run the ETL and detection pipelines that process it, and architect the extraction of complex data from mobile forensic artefacts.

You'll work hand in hand with our research team, implementing their prototypes, productionizing their detection logic, and building the tooling and data access they need to go deeper. This is a role for a strong backend engineer who enjoys hard data problems: high-volume ingestion, messy real-world artefacts, and pipelines that have to be both fast and correct.

The stack is fully Python, running on AWS Fargate, EC2, and Serverless.

Key Responsibilities

• Data Ingestion at Scale: Design, build, and operate pipelines that ingest large volumes of telemetry from mobile endpoints reliably and efficiently.
• ETL & Detection Pipelines: Build and maintain the ETL processes that transform raw data, and implement the detection logic that runs across it to surface threats.
• Forensic Artefact Extraction: Architect the extraction and parsing of complex data from mobile forensic artefacts, handling the varied and often undocumented structures these artefacts contain.
• Partnering with Research: Work closely with the research team to implement their prototypes in production, translate their detection ideas into robust pipeline logic, and build the data access and tooling they need to uncover mobile spyware.
• Scalability & Reliability: Ensure the data platform performs at scale, optimizing throughput, query performance, and cost across large datasets, with strong reliability and fault tolerance.
• Data Quality & Observability: Build monitoring, validation, and error-handling into the pipelines so data issues are caught early and the system is observable end to end.
• Day-to-Day Activities
• Build and maintain high-volume ingestion and ETL pipelines in Python
• Implement and productionize detection logic from research prototypes
• Design parsers and extraction logic for complex mobile forensic artefacts, accommodating evolving data formats and schema changes
• Optimize data storage and query performance across large datasets
• Deploy and operate services on AWS Fargate, EC2, and Serverless
• Collaborate directly with researchers to understand what they need and build it
• Establish monitoring, alerting and data quality checks to detect issues and ensure pipeline reliability
• Contribute to architectural decisions on how data flows through the platform

Requirements

• 5+ years of backend engineering experience, with strong Python skills
• Proven experience ingesting and processing large volumes of data at scale
• Strong experience building ETL pipelines and working with high-volume data systems
• Hands-on experience deploying and operating services on AWS (Fargate, EC2, Serverless/Lambda) or the equivalent on GCP or Azure
• Solid understanding of data modelling, pipeline design, and performance optimization
• Experience building reliable, observable, fault-tolerant systems in production
• Strong problem-solving skills and comfort working with messy, real-world data
• Ability to collaborate closely with non-engineering teams and turn prototypes into production systems
• Nice-to-Have
• Experience with ClickHouse or Snowflake (highly preferred)
• Experience with columnar data stores and analytical query optimization
• Familiarity with event-driven or streaming architectures (Kafka, SQS, SNS, Kinesis, or Pub/Sub)
• Experience parsing binary formats, log data, or forensic artefacts
• Background in mobile security, threat detection, or digital forensics
• Experience working alongside research or data science teams
• Experience developing and deploying software in on-premises environments, with an understanding of the operational challenges they present