Billing Operations Specialist

Sorry, this job was removed at 07:06 p.m. (CST) on Friday, Dec 13, 2024
3 Locations
In-Office or Remote
140K-160K Annually
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the Role

We are seeking a detail-oriented and analytical Billing Operations Specialist to join our growing billing and monetization team. In this role, you will be instrumental in managing and optimizing our customer billing processes, ensuring accuracy, efficiency, and customer satisfaction. This role is a great fit for someone who’s both seen excellence at scale and operated in rapidly scaling, high-ambiguity environments. 

Responsibilities:

  • Collaborate with product, engineering, and payments fraud teams to:
    • Conduct root cause analysis on billing errors and defects
    • Identify and implement process improvements
    • Automate billing processes for increased efficiency
  • Generate and analyze reports on billing performance and trends to drive continuous improvement
  • Manage relationships with third-party partners to maintain up-to-date listings and resolve customer billing issues
  • Partner with Finance and Go-to-Market teams to address user inquiries related to onboarding, billing, and collections
  • Provide training and support to the product support team on customer billing inquiries
  • Oversee communication with customers and external partners regarding billing and credit inquiries

You may be a good fit if you have:

  • 3+ years of experience in financial or billing operations, preferably in high-volume SaaS environments
  • Strong working knowledge of billing systems, subscription management, and invoicing tools
  • Experience with Stripe and Metronome is a plus
  • Excellent analytical and problem-solving skills
  • An ability to thrive in fast-paced, high-volume, and ambiguous environments
  • Strong project management skills
  • Comfort with behind-the-scenes work that is essential and highly valuable, though at times unglamorous

The expected salary range for this position is:

Annual Salary:

$140,000$160,000 USD

Logistics

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.

Anthropic Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.

  • Strong & Reliable Incentives Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
  • Healthcare Strength Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
  • Parental & Family Support Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.

Anthropic Insights

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The Company
HQ: San Francisco, California
2,500 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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