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Ridgeline

AI-native front-to-back office investment platform

Staff Infrastructure Security Engineer

Security Engineering & ArchitecturePosted on Nov 11
Full-time

About the Job

Requirements

  • At least 8 years of relevant experience in cloud security or platform engineering, including independently defining and executing complex projects from planning to production and leading initiatives across multiple teams.
  • Expert proficiency in at least one programming language; Python is strongly preferred, with Go, Kotlin, or TypeScript as additional options.
  • Experience with AWS, including Identity and Access Management (IAM, Organizations and Service Control Policies, and Identity Center); networking (VPC, Security Groups, Transit Gateway, and Load Balancers); compute (EKS); data persistence (S3, Aurora, and DynamoDB); and logging and monitoring (CloudTrail and CloudWatch).
  • Recognized expertise in AWS security and cloud security specialties, including identity, detection, networking, data security, containers and serverless, and governance.
  • Demonstrated success designing, implementing, and scaling access-management strategies and policy frameworks, including IAM and Service Control Policies.
  • Deep understanding of cloud workload protection, infrastructure monitoring, and threat detection in AWS-native environments, including identity chaining, cross-account lateral movement, control-plane and data-plane separation failures, and supply-chain risks that automated tooling may miss.
  • Fluency with infrastructure as code, such as Terraform, and CI/CD practices.
  • Experience leading high-impact cloud security incidents as a technical lead or incident commander and driving findings through remediation.
  • Experience building cloud security platforms, detection pipelines, or posture management at organizational scale, with a track record of reducing false positives.
  • Experience designing AI-augmented security workflows or lightweight agents and automations, with sound judgment about responsible AI experimentation and data use.
  • Strong written and verbal communication skills to explain security tradeoffs clearly to engineers, product partners, and executive stakeholders, and to influence through technical credibility.
  • Demonstrated ability to make sound architectural tradeoffs across multiple services, improve long-term code and system health, and align stakeholders when changes have cross-team impact.

Responsibilities

  • Drive secure-by-default cloud architecture across product areas; threat-model new infrastructure designs and service adoptions, and define security requirements that eliminate risk classes before systems are built.
  • Identify complex cloud security risks missed by tooling, including identity chaining, cross-account lateral movement, control-plane and data-plane separation failures, and supply-chain risks; perform variant analysis to eradicate risk classes across the cloud environment.
  • Design AI-augmented analysis workflows that combine manual expertise with automated detection to find risks at scale.
  • Lead high-impact cloud incidents as technical lead or incident commander.
  • Drive findings to remediation by assessing real-world exploitability, calibrating risk, and building systemic fixes that reduce risk over time; use AI to identify patterns across historical findings that reveal systemic weaknesses.
  • Own or lead development of advanced cloud security platforms that scale across the organization, including AWS guardrails and controls such as Service Control Policies, IAM boundaries, AWS-managed security services, custom-built solutions, and policy as code.
  • Architect AI-powered detection and posture-management pipelines that reduce manual effort while maintaining accuracy and reducing false positives.
  • Embed security into CI/CD and infrastructure automation to ensure reproducible, testable, and auditable deployments.
  • Lead the strategy for access management, least-privilege enforcement, encryption and key management, and runtime protections across the platform.
  • Build and champion frameworks for secure platform integrations with third-party cloud services and internal tools.
  • Shape cloud security decisions across multiple engineering organizations; partner with Staff+ engineers and platform teams on design, and influence through technical credibility rather than policy mandates.
  • Define and execute complex cross-functional projects from planning to production, deliver within deadlines, manage expectations as plans change, and prioritize work spanning multiple cycles.
  • Set team standards for effective and responsible AI use in cloud security workflows, including responsible experimentation and data use; build lightweight agents and automations that accelerate team outcomes.

Desired Qualifications

  • Python is strongly preferred; Go, Kotlin, and TypeScript are additional programming language options.

About the Company

Ridgeline

AI-native front-to-back office investment platform

Ridgeline delivers a single, cloud-based platform for investment management that unifies front-to-back office functions (client engagement, portfolio management, trading, compliance, reconciliation, accounting, and reporting) on one real-time data set. Its AI-native approach embeds Ridgeline AI throughout the platform, including digital coworkers, a conversational reporting assistant, and workflow automation, plus Market Intelligence integrated into workflows. It distinguishes itself from competitors by building the system from the ground up with an enterprise software approach and tying pricing to multi-year SaaS contracts that scale with assets under management. The company aims to help asset managers, wealth managers, and RIAs run their businesses more efficiently, reduce data silos, automate complex workflows, stay compliant, and produce timely financial reporting.

Company size
201-500
Company stage
Series E
Total funding
$250M
Headquarters
Incline Village-Crystal Bay, Nevada
Founded
2018

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