Billing, Identity and Fraud Engineering Manager

Posted 3 Days Ago
Be an Early Applicant
San Francisco, CA
7+ Years Experience
Software
The Role
As a Billing, Identity and Fraud Engineering Manager, you will lead a team to enhance cloud billing capabilities, implement security measures, develop customer profile infrastructure, ensure system compliance, and manage project delivery while maintaining high standards of code quality and system reliability.
Summary Generated by Built In

Lambda was founded in 2012 by AI engineers who published research at top machine learning conferences. We aim to be the leading AI computing platform, supporting developers throughout the entire AI development lifecycle. At Lambda, we empower AI engineers to easily, securely, and affordably build, test, and deploy AI products at scale. Our offerings include high-performance on-prem GPU hardware and flexible cloud-based GPU solutions. We aim to make access to powerful computation as effortless and ubiquitous as electricity.

If you'd like to build the world's best deep learning cloud, join us.

Note: This position requires presence in one of our San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

What You’ll Do

  • Hire and lead a team of engineers responsible for usage-based billing, account management, PII controls, etc.
  • Level up our cloud billing capabilities, including implementing tiered pricing, multi-currency support, complex discounting structures, enterprise agreements, etc.
  • Lead our anti-fraud initiatives from a technical perspective
  • Build a robust customer profile infrastructure, aggregating data from multiple systems
  • Leverage monitoring and observability tools to maintain, improve, and expand our event-based billing pipelines to be robust, scalable, auditable, and high-volume
  • Work with our Security team to ensure the safety of systems handling sensitive customer information and financial data
  • Drive the implementation and maintenance of compliance standards including SOC2, SOX, and ISO for billing pipelines and customer data
  • Collaborate with cross-functional teams spanning Product, Revops, Sales, Analytics, and Accounting
  • Develop and enforce best practices for code quality, security, and performance
  • Manage project timelines, resources, and deliverables to meet organizational goals
  • Continuously evaluate and improve system performance, reliability, and security
  • Participate in audits and risk assessments to ensure compliance with regulatory requirements
  • Stay current with industry trends and emerging technologies to drive innovation within the team
  • Implement and support engineering best practices within the team (including code reviews, testing, etc) and drive operational excellence
  • Provide technical guidance and mentorship to foster a culture of continuous learning and growth

You

  • Have 8+ years of experience in software engineering, with at least 3+ years in a leadership role
  • Have a strong understanding of the technical and legal requirements around financial data processing
  • Have hands-on experience implementing and maintaining compliance standards (SOC2, SOX, ISO, etc.)
  • Exhibit excellent knowledge of data security practices, particularly related to PII and financial information
  • Are well-versed in fraud prevention techniques and risk management in digital environments
  • Have a track record of successfully leading engineering teams and delivering complex projects
  • Possess strong communication skills, able to effectively interact with both technical and non-technical stakeholders
  • Demonstrate a strategic mindset, capable of aligning technical decisions with business goals
  • Are familiar with the requirements and challenges involved in preparing a company for an IPO
  • Hold a Bachelor's degree in Computer Science, Software Engineering, or a related field (Master's preferred)
  • Are adaptable and thrive in a fast-paced, constantly evolving environment

Nice to Have

  • Experience in the machine learning or computer hardware industry
  • Possess deep technical knowledge of cloud-based architectures, preferably with experience in systems similar to AWS

Salary Range Information 

Based on market data and other factors, the salary range for this position is $177,000- $255,000. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. 

About Lambda

  • We offer generous cash & equity compensation
  • Investors include Gradient Ventures, Google’s AI-focused venture fund
  • We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability
  • Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
  • We have a wildly talented team of 300, and growing fast
  • Health, dental, and vision coverage for you and your dependents
  • Commuter/Work from home stipends for select roles
  • 401k Plan with 2% company match
  • Flexible Paid Time Off Plan that we all actually use

A Final Note:

You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.

Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Top Skills

Software Engineering
The Company
HQ: San Francisco, CA
106 Employees
Hybrid Workplace
Year Founded: 2012

What We Do

Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.

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