We are hiring a Product Engineer to help build the next generation of an AI-native Cloud Security and Compliance platform. This is a high-impact role for someone who can operate across product, engineering, AI systems, cloud security, compliance, and platform architecture and help define both the platform and the category we are building.

We are building a unified system that helps organizations:

while also enabling them to:

Understand security risk - Predict threats - Decide actions - Automate remediation

This role exists to ensure we build that system correctly and create a scalable, secure, and enterprise-ready platform that simplifies cloud governance, compliance, security operations, and audit readiness across multi-cloud environments.

What We Are Looking For:
You likely have experience in:

Enterprise SaaS platforms or security product companies

Cloud security, governance, compliance, or cyber risk management products

Security domains such as IAM, cloud security, CSPM, CIEM, SIEM, EDR, exposure management, or vulnerability management

Compliance automation and governance platforms

AI/ML-driven products, data platforms, or intelligent automation systems

Multi-cloud environments (AWS, Azure, GCP, DigitalOcean)

Security and compliance frameworks such as SOC 2, ISO 27001, CIS, NIST, and PCI DS

Distributed systems and platform architecture

You should be robust in:

Systems thinking and platform design

Cloud security and governance fundamentals

Security threat modeling and adversarial thinking

Compliance and audit workflows

AI-native product design and intelligent automation

API design and integration architecture

Working across product, engineering, customer success, security, and GTM team

What You Will Do:
You will design and build the core systems behind our platform, including:

Compliance Assessment and Monitoring

Cloud resource discovery and inventory management across multiple cloud providers

Compliance assessment and continuous monitoring systems

Security control validation and framework-to-control mapping

Findings generation,



risk categorization, and remediation workflows

Historical compliance tracking and governance analytics

AI-powered security intelligence systems for risk scoring, prioritization, prediction, and automation

Security data graph connecting identities, assets, resources, controls, findings, exposures, and risk relationships

Attack path analysis and adversarial modeling capabilities

Threat prediction and security posture analysis systems

Intelligent recommendations and decision-support workflows

Evidence and Audit Readiness

Evidence collection and audit artifact management

Evidence traceability, lineage, and control mapping

Audit readiness workflows and reporting systemsAutomated evidence generation and compliance documentation

Autonomous Security Operations

Agent-based workflows for compliance validation and security operations

Autonomous remediation and orchestration capabilities

Automated policy enforcement and governance controls

Risk-based prioritization and workflow automation

Secure cloud onboarding and integration experiences

Multi-cloud integrations with AWS, Azure, GCP, and DigitalOcean

Multi-tenant SaaS architecture and organizational isolation

Identity, access management, and RBAC capabilities

esInternal APIs and ecosystem integrations

Reporting and Analytics

Executive compliance and security dashboards

Compliance posture visualization and governance reporting

Security risk and exposure analytics

Trend analysis, historical reporting, and audit-ready reporting

Platform observability and operational intelligence

Platform Infrastructure

Scalable SaaS platform architecture for enterprise customers





Service-oriented and distributed systems architecture

Secure data management and storage

Reliability, performance, monitoring, and operational excellence

APIs and integrations that power the ecosystem

You Will Also Help Define:

Product strategy and 3-5 year platform direction

Compliance, governance, and security product roadmap

AI-native security and compliance platform evolution

Multi-cloud platform expansion strategy

Platform Architect

Service boundaries and platform evolution

Data plane, control plane, and security architecture

Security and compliance design standards

Scalability, reliability, and operational excellence initiatives

Category and Market Position

Category positioning in enterprise cybersecurity

Cloud compliance and governance market strategy

AI-native security operations and automation strategyPlatform differentiation in the compliance automation and cloud security markets

Customer, security team, and auditor experience improvements

Build vs buy vs partner decisions across the portfolio

What Success Looks Like:

Customers continuously monitor compliance posture across cloud environments

Security risks, findings, and exposures are identified, prioritized, and contextualized automatically.

Audit evidence is collected and organized with minimal manual effort

Findings are actionable, traceable, and mapped to compliance requirements

AI systems help security and compliance teams make faster, more informed decisions

Autonomous workflows reduce manual governance and remediation effort

The platform scales securely across multiple organizations and cloud providers

Compliance teams, security teams, executives, and auditors can efficiently access the information they need.

Organizations achieve stronger governance, improved security posture, and faster audit readiness.

The platform becomes a category-defining solution at the intersection of cloud security, compliance automation, AI-driven risk management, and enterprise cybersecurity.

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📌 Technical Product Manager (Ontario)
🏢 TAC Security
📍 Ontario