Senior Application Security Engineer
M&T BankSalary not specified
Full Time
Senior (5 to 8 years), Expert & Leadership (9+ years)
Not SpecifiedCompensation
N/AExperience Level
N/AJob Type
Not SpecifiedVisa
N/AIndustries
Requirements
- Experience creating, building, or scaling an application security program in a cloud-first organization
- Primary coding language: Javascript (NodeJS/Typescript) and Python
- Experience with threat modeling and architecture reviews
- Experience working with engineering and technical leadership to build security processes like vulnerability management
- Deep understanding of web and API-based security vulnerabilities
Responsibilities
- Choosing the right App Sec tools for the environment to make code secure before it is shipped
- Creating and maturing processes around vulnerability management, architecture reviews, pentesting, and threat modeling
- Doing code reviews and bug fixing
- Helping build and POC new secure ways of writing code (validation libraries, authentication/authorization practices, encryption SDKs)
- Helping re-imagine permissioning and authorization for users of the Latent platform
- Working alongside engineers to balance business requirements with security controls
- Creating a mature pentesting and/or bug bounty program
- Bringing security checks and tooling to developer workflows (AI-based IDEs, CI/CD, etc.)
Skills
Latent AI
Optimizes AI for edge computing applications
About Latent AI
Latent AI focuses on enhancing artificial intelligence for edge computing, which involves processing data close to where it is generated, like on smartphones and IoT devices. Their main product is an edge MLOps workflow that automates and simplifies the deployment of AI models on these devices, ensuring they are efficient, secure, and require minimal maintenance. This company stands out from competitors by specifically targeting the edge computing market and providing a software development kit (SDK) called Latent LEIP, which aids developers in creating and deploying AI models. The goal of Latent AI is to make AI more accessible and efficient for applications that need real-time data processing, such as in autonomous vehicles and smart cities.
Menlo Park, CaliforniaHeadquarters
2018Year Founded
$21.9MTotal Funding
SERIES_ACompany Stage
Automotive & Transportation, Enterprise Software, AI & Machine LearningIndustries
51-200Employees
Risks
Competition from tech giants like Google and Amazon threatens Latent AI's market share.
Rapid AI advancements may outpace Latent AI's current capabilities, requiring continuous innovation.
Dependency on key partnerships, like Booz Allen, poses risks if relationships change.
Differentiation
Latent AI specializes in optimizing AI for edge computing applications.
Their edge MLOps workflow ensures efficient, secure AI model deployment on edge devices.
Latent AI's SDK, Latent LEIP, streamlines AI model creation and deployment for developers.
Upsides
Growing interest in federated learning enhances privacy and efficiency for edge AI.
The rise of TinyML aligns with Latent AI's focus on resource-constrained edge devices.
5G technology adoption boosts data transmission speed for Latent AI's solutions.
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