Senior Enterprise Risk Manager at Lambda

San Francisco, California, United States

Apply Now

$244,000 – $340,000Compensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI Infrastructure, Cloud Computing, TechnologyIndustries

Requirements

10+ years of risk management experience, ideally in cloud infrastructure, financial services, or large-scale technology/energy industries
Deep knowledge of ERM frameworks (e.g., COSO, ISO 31000) and risk management best practices
Ability to present key initiatives to executive leadership and Board and drive strategic decisions regarding risk management
Strong analytical skills
Executive presence and credibility to advise executives and the Board on risk strategy

Responsibilities

Design and implement Lambda’s Enterprise Risk Management (ERM) framework, policies and governance aligned with rapid AI infrastructure scaling
Drive risk culture and awareness across all business units
Assess risks related to large-scale data center procurement, long-term customer contracts, and multi-billion-dollar financing structures
Partner with Finance on capital markets risk (debt, liquidity, interest rates, covenants) and with Operations on construction, vendor, and supply chain risks
Monitor external risks such as regulatory shifts, geopolitical uncertainty, and evolving AI industry dynamics
Oversee enterprise-wide risk assessments, including emerging risks and strategic threats
Evaluate business processes, controls, and external environment to identify potential vulnerabilities
Define risk appetite and tolerance levels, ensuring alignment with growth objectives and stakeholder expectations (including Lambda’s board)
Develop metrics and risk appetite/tolerance statements
Build a risk dashboard for executives and the Board, highlighting exposures, mitigation strategies, and emerging threats
Provide regular reporting to executive leadership, the Audit & Risk Committee, and the Board on key risks, trends, and mitigation strategies
Act as a trusted advisor to executives, business and functional leaders, ensuring risks are considered in strategic initiatives, new products, major contracts, financings and large-scale projects
Lead scenario analyses (e.g., supply chain disruptions, interest rate spikes, power shortages) to stress-test the business model
Ensure business continuity planning is robust and scalable
Lead scenario planning, stress testing, and contingency planning exercises
Ensure compliance with regulatory expectations related to risk governance
Attract, mentor and grow risk professionals while building a culture of accountability and risk awareness across Lambda

Skills

Enterprise Risk Management

ERM Framework

Risk Assessment

Risk Mitigation

Strategic Risk

Financial Risk

Operational Risk

Compliance Risk

Capital Markets Risk

Data Center Procurement

Governance

Risk Culture

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.

Land your dream remote job 3x faster with AI

Try Jobo Free