Security Engineer - Architecture at Lambda

San Francisco, California, United States

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$296,000 – $445,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Cloud ComputingIndustries

Requirements

Ability to design and document comprehensive security patterns, standards, and implementation guides
Experience conducting security design reviews and developing threat models for critical systems
Skills in creating clear security requirements and acceptance criteria for engineering teams
Capability to prototype and implement security controls, tools, and automation
Familiarity with leveraging LLMs or AI for security capabilities like automated threat modeling and AI-assisted reviews
Strong collaboration skills with Product Engineering, Platform Engineering, and Technical Program Managers
Ability to develop customer-facing security documentation, architecture whitepapers, and technical content
Experience mentoring or coaching engineers on secure design principles

Responsibilities

Drive Security Architecture: Design and document comprehensive security patterns, standards, and implementation guides that engineering teams can adopt to build secure-by-default systems
Lead Security Reviews: Conduct security design reviews and develop threat models for critical systems, identifying risks and providing actionable recommendations
Develop Security Requirements: Create clear security requirements and acceptance criteria that integrate seamlessly into engineering development cycles
Build Security Solutions: Prototype and implement security controls, tools, and automation that demonstrate secure patterns and enable self-service security
Pioneer AI-Powered Architecture: Leverage Lambda's hosted LLMs to build next-generation security capabilities including automated threat modeling, AI-assisted security reviews, and intelligent architecture recommendations
Collaborate Across Engineering: Partner with Product and Platform Engineering teams to integrate security architecture requirements into their designs at optimal moments
Enable Customer Trust: Develop customer-facing security documentation, architecture whitepapers, and technical security content that demonstrates security maturity
Mentor Security Excellence: Coach engineers across the organization on secure design principles

Skills

Security Architecture

Threat Modeling

Security Design Reviews

Security Requirements

AI Infrastructure

LLM Security

Cloud Security

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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