DataVisor

Real-time fraud detection & risk management

Security Engineer

Security Engineering & Architecture +1Confirmed live in the last 24 hours

Full-timeMountain View, CA, USA

About the Job

Requirements

A bachelor's degree in Computer Science, Information Security, or a related technical field is required.
At least 5 years of security engineering experience, including at least 2 years focused specifically on AI/ML security.
Hands-on experience securing AWS and GCP environments, including core services such as IAM, EC2, S3, and VPC, and their GCP equivalents: IAM, Compute Engine, Cloud Storage, and VPC.
Experience with cloud security posture management (CSPM) for continuous detection and remediation of cloud misconfigurations.
Experience securing AI/LLM deployments in cloud environments, including deploying and hardening foundation models such as Claude on AWS (e.g., Amazon Bedrock) with guardrails, input/output filtering, prompt-injection defense, output validation, and data-egress controls.
Hands-on assessment of Model Context Protocol (MCP) and LLM connector integrations against OWASP guidance, covering prompt injection, cross-connector chaining, OAuth scope minimization, tool-access boundaries, and untrusted-content handling.
Working knowledge of AI security frameworks and standards: NIST AI Risk Management Framework, OWASP LLM Top 10, OWASP guidance for MCP and agentic systems, and MITRE ATLAS.
Ability to threat-model and risk-assess AI systems, agentic workflows, and third-party AI integrations prior to approval.
Understanding of core security concepts—cryptography, authentication, authorization, security protocols, and vulnerability classes—as applied to web application and cloud service security.
Deep technical understanding of common security vulnerabilities and risks, along with countermeasures and compensating controls.
A solid grasp of IP networking protocols, including IPv4/IPv6, TCP/UDP, DHCP, HTTPS, FTP, and similar protocols.

Responsibilities

Assess and secure AI/LLM deployments and integrations, including Model Context Protocol and other LLM connector requests, through threat modeling, guardrail design, and risk assessment prior to approval.
Perform daily security monitoring across cloud and infrastructure, covering cloud security posture management, SIEM and log analysis, cloud-native threat detection, database activity monitoring, and security orchestration, automation, and response.
Use SIEM tooling for real-time analysis of security alerts generated by cloud infrastructure and applications.
Own security for the AWS and GCP environments, including IAM, compute, storage, networking, and workload configurations; harden the footprint, enforce baselines, and remediate misconfigurations and vulnerabilities across both clouds.
Participate in incident management, change management, security policy management, and security incident response.
Contribute to SOC 2, PCI DSS, and ISO 27001 compliance programs.

Security Engineer

DataVisor · Mountain View, United States (Remote) · Full-time · Posted 2026-08-21

Salary: USD 120,000–150,000

Workplace: remote

Department: Engineering

Description

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's solution scales infinitely and enables organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine and investigation tools work together to provide guaranteed performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering the total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results driven. Come join us!

We are seeking a Security Engineer who possesses expertise in cloud environments and a strong focus on securing AI/LLM deployments. You will be part of a team that protects system boundaries, keeps computer systems and network services hardened against attacks, and secures sensitive data. You will collaborate closely with our team to ensure that our products, cloud environments, and AI integrations are built to industry security standards and best practices.

RESPONSIBILITIES

Assess and secure AI/LLM deployments and integrations — including Model Context Protocol (MCP) and other LLM connector requests — through threat modeling, guardrail design, and risk assessment prior to approval
Perform daily security monitoring across cloud and infrastructure, spanning cloud security posture management (CSPM), SIEM and log analysis, cloud-native threat detection, database activity monitoring, and security orchestration, automation, and response (SOAR)
Leverage SIEM tooling for real-time analysis of security alerts generated by our cloud infrastructure and applications
Own the security of our entire AWS and GCP environments — including IAM, compute, storage, networking, and workload configurations — hardening the footprint, enforcing baselines, and remediating misconfigurations and vulnerabilities across both clouds
Participate in incident management, change management, security policy management, and security incident response
Contribute to SOC 2, PCI DSS, and ISO 27001 compliance programs

Requirements

Bachelor's degree in Computer Science, Information Security, or a related technical field
5+ years of security engineering experience, including at least 2 years focused specifically on AI/ML security
Hands-on experience securing AWS and GCP environments, including core services such as IAM, EC2, S3, VPC, and their GCP equivalents (IAM, Compute Engine, Cloud Storage, VPC)
Experience with CSPM for continuous detection and remediation of cloud misconfigurations
Experience securing AI/LLM deployments in cloud environments — including deploying and hardening foundation models such as Claude on AWS (e.g., Amazon Bedrock) with guardrails, input/output filtering, prompt-injection defense, output validation, and data-egress controls
Hands-on assessment of MCP and LLM connector integrations against OWASP guidance — covering prompt injection, cross-connector chaining, OAuth scope minimization, tool-access boundaries, and untrusted-content handling
Working knowledge of AI security frameworks and standards: NIST AI RMF, OWASP LLM Top 10, OWASP guidance for MCP and agentic systems, and MITRE ATLAS
Ability to threat-model and risk-assess AI systems, agentic workflows, and third-party AI integrations prior to approval
Understanding of core security concepts — cryptography, authentication, authorization, security protocols, and vulnerability classes — as applied to web application and cloud service security
Deep technical understanding of common security vulnerabilities and risks, along with countermeasures and compensating controls
Solid grasp of IP networking protocols: IPv4/IPv6, TCP/UDP, DHCP, HTTPS, FTP, and similar

Benefits

Salary ranges between USD 120,000 -150,000 /year
Total compensation includes base salary, performance bonuses, and equity options.
Comprehensive medical, dental, and vision insurance coverage.
401(k) retirement savings plan available.
Discretionary paid time Off (DTO) plus paid holidays.
Remote work may be considered for candidates located outside a 50-mile radius of Mountain View.

Apply

Apply at DataVisor

About the Company

DataVisor

Real-time fraud detection & risk management

DataVisor offers a fraud detection and risk management platform for fintech and cybersecurity, helping financial institutions, e-commerce platforms, and online services detect and prevent fraudulent activity in real time. The core product integrates with clients’ existing data systems through APIs, supporting real-time or batch data processing to identify suspicious patterns. Machine learning analyzes large datasets to spot indicators of fraud and continuously improve detection accuracy. The company differentiates itself by providing a flexible, API-based integration that fits into clients’ current workflows and data environments, enabling real-time prevention across diverse use cases. Revenue comes from a subscription model that gives clients ongoing access to the platform and updates. The goal is to help organizations protect their operations and customers by staying ahead of increasingly sophisticated fraud schemes.

Company size: 51-200
Company stage: Late Stage VC
Total funding: $94.5M
Headquarters: Mountain View, CA
Founded: 2013

Recently Posted Jobs

Explore more opportunities at DataVisor

See more jobs