Simplify Logo

Full-Time

Lead Devsecops Engineer

Updated on 9/6/2024

Relyance AI

Relyance AI

51-200 employees

Data protection and privacy compliance platform

Data & Analytics
Consulting
AI & Machine Learning
Legal

Compensation Overview

$170k - $200kAnnually

Senior, Expert

San Francisco, CA, USA

Category
DevOps & Infrastructure
DevOps Engineering
Required Skills
Bash
Kubernetes
Python
Airflow
Git
BigQuery
Go
Terraform
Google Cloud Platform
Requirements
  • Strong CI/CD pipeline experience, including proficiency in tools like Github Actions
  • Deep understanding of CI/CD best practices and can effectively automate build, test, and deployment processes.
  • Track record of building scalable and multi-region (for high-availability) infrastructure components on public cloud-based platforms like Google Cloud Platform (GCP).
  • Comfortability with programming languages like Python, GoLang, and scripting languages like bash.
  • Comfortability with orchestration platforms like Kubernetes and Airflow.
  • Familiarity with Infrastructure-as-Code technologies like terraform.
  • Awareness of cloud-networking technologies like Virtual Private Cloud (VPC), subnets, firewall rules, network routing rules, network peering.
  • Proficiency with public cloud concepts and delivering working solutions on public cloud infrastructure, preferably GCP (BigQuery, BigTable, Pub/Sub, SecretManager).
  • Strong software engineering skills, and experience writing clear, concise, and maintainable code considering design principles and applying sound testing practices.
  • Systematic and goal-directed approach to project management; are comfortable dealing with ambiguity and ruthlessly prioritizing and managing your time with a sense of urgency.
Responsibilities
  • Advocating engineering best practices, code reviews and automated unit/end-to-end testing and deployment to stage and production systems.
  • Optimizing all cloud-based infrastructure environments to control overall costs.
  • Defining Service-Level Objectives (SLO) and track Service-Level Indicators (SLI) for all components running in a cloud-infrastructure environment.
  • Automating deployment of cloud-infrastructure components using Infrastructure-as-Code to deliver services at high velocity.
  • Designing and implementing a good observability and alerting framework for detecting any problems and avoiding downtime for Relyance AI’s customers.
  • Planning, architecting and building networking topologies to allow cloud-infrastructure components to securely communicate with each other.
  • Monitoring and resolving high, medium, and low vulnerabilities or threats detected in source-code and cloud-infrastructure within defined Service-Level Agreements timeframe.
  • Setting up policies and framework in cloud-based environment for secure access to production environment with least-privilege principle.
  • Shaping the direction of infrastructure at Relyance and building a cohesive team culture of ownership, growth, transparency, and customer focus.

Relyance AI specializes in data protection and privacy compliance by using machine learning to track personal data flows within organizations. Their software-as-a-service platform provides real-time monitoring and insights, helping clients, such as tech companies and healthcare providers, ensure compliance with privacy regulations. What makes Relyance AI different is its focus on automating data tracking, which reduces manual workflows and compliance risks. The company's goal is to help organizations maintain user trust and meet regulatory requirements effectively.

Company Stage

Series A

Total Funding

$35M

Headquarters

Mountain View, California

Founded

2020

Growth & Insights
Headcount

6 month growth

-4%

1 year growth

-1%

2 year growth

4%
Simplify Jobs

Simplify's Take

What believers are saying

  • Recognition as a Gartner Cool Vendor and inclusion in CB Insights’ AI 100 Global List highlight Relyance AI's innovative edge and market potential.
  • The company's participation as a finalist in RSA's Innovation Sandbox contest underscores its industry recognition and potential for rapid growth.
  • Relyance AI's SaaS model and machine learning capabilities offer scalable solutions that can adapt to the evolving needs of highly regulated industries.

What critics are saying

  • The highly competitive data protection and privacy compliance market may pressure Relyance AI to continuously innovate to maintain its edge.
  • Dependence on machine learning models requires constant updates and improvements to stay effective against emerging data privacy challenges.

What makes Relyance AI unique

  • Relyance AI's machine learning-driven platform offers real-time data flow mapping and compliance management, setting it apart from traditional manual compliance methods.
  • Their focus on code-level privacy compliance ensures a deeper and more accurate understanding of data processing activities, unlike competitors who may not offer such granular insights.
  • The integration of Asset Intelligence and Data Security Posture Management provides unprecedented clarity and control over sensitive data, a unique feature in the data protection landscape.