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BforeAI
BforeAI
51 – 200 Darbinieki
FinansesKiberdrošībaMākslīgais intelekts
BforeAI develops predictive cybersecurity tools designed to disrupt online threats before they reach businesses. Its PreCrime™ platform uses behavioral analytics and artificial intelligence to identify suspicious domain activity and autonomously predict, block, and preempt phishing, spoofing, impersonation, hijacking, ransomware, online fraud, and data exfiltration. The platform is built to work with existing security systems and serves organizations across sectors including finance, manufacturing, retail, and media. BforeAI focuses on reducing the financial and reputational harm caused by malicious online activity; the company was named a 2024 Gartner Cool Vendor for AI in Banking & Investment Services.
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Vakances uzņēmumā

Senior Engineering Manager, Security Research at BforeAI (Argentina Remote)

Lead SaaS engineering and security research teams at BforeAI, turning threat intelligence into production detections and customer features.

ARArgentīnaAttālinātiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuInženierijas vadītājs
AzureGoKafkaKubernetesMākonisNeo4jPostgresPythonRedis

Apraksts

  • Lead Software Engineering and Security Research Engineering as a hands-on manager.
  • Hire and onboard team members, manage performance and career growth, and oversee delivery.
  • Turn threat research and shared data capabilities into production detections and customer features.
  • Work with engineers and researchers on validation, design choices, and production issues.
  • Guide work from research hypothesis and evaluation through implementation, release, and ongoing detection quality.
  • Set research priorities with Product and engineering leaders.
  • Validate evidence, identify coverage gaps, and assess production readiness.
  • Partner on services, APIs, detection integration, testing, and production troubleshooting.
  • Create detection evaluation and regression testing practices; monitor false positives, missed threats, coverage, and production behavior.
  • Define research goals and evaluation criteria, then agree on implementation commitments.
  • Plan delivery with Product around interfaces, acceptance criteria, dependencies, and capacity.
  • Coordinate data access, interfaces, and reliability with Platform Engineering while maintaining customer data access boundaries.
  • Shape product and detection designs to reuse shared evidence, relationships, and history across customer workflows.
  • Grow technical leads and independent ownership, adjusting team structure as the team expands.
  • Handle customer escalations and production problems that call for engineering and research expertise.
  • Support AI-assisted engineering and research by evaluating and reviewing outcomes.

Prasības

  • Has led development of SaaS products or products built on shared data platforms.
  • Has directly managed threat intelligence, threat research, detection engineering, or vulnerability research teams whose work contributed to a production security product.
  • Has led software engineering delivery and managed technical contributors across engineering and research disciplines.
  • Can point to research findings translated into shipped capabilities, including validation, testing, deployment, and continued quality improvement.
  • Brings technical depth in software engineering and threat research, including architecture, detection methods, and data quality.
  • Has owned hiring, performance management, and career development for a multidisciplinary team.
  • Can manage research uncertainty while setting clear delivery expectations and balancing exploration with customer commitments.
  • Can document decisions and coordinate engineering and research delivery in a remote team.
  • Willing to learn and use AI-augmented engineering and research practices.
  • Experience with external threat intelligence, phishing, malicious domains, impersonation, or adversarial infrastructure analysis is helpful.
  • Experience developing technical leads and expanding delegated ownership as a team grows is helpful.
  • A software development background, particularly in Python or Go, is helpful.
  • Experience with cloud services, event-driven systems, graph-based analysis, or evaluation of ML-assisted detections is helpful.
  • Experience using AI development or research tools with measurable quality controls is helpful.
  • Understands engineering principles behind Go, Python, Event Hubs, Kafka-compatible messaging, Azure Data Lake Storage, Azure Data Explorer, PostgreSQL, Neo4j, Redis, Databricks, Kubernetes, and Azure-managed compute services.
  • Must be authorized to work in the country of residence; visa sponsorship is not available for this role.

Priekšrocības

  • Flexible time off.
  • Sick days.
  • All public holidays.
  • Stock options.
  • Benefits tailored to the country where you will work.
  • Reasonable accommodations for qualified individuals with disabilities as needed.

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