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.
We believe that partnering with governments will be integral to our mission of developing advanced AI for the long-term benefit of humankind, and we’re seeking our first Commercial Counsel specializing in government contracts to serve as a key architect of our public sector agreements. You'll be a strategic partner to both our policy team, designing and negotiating pioneering agreements for governments to “red team” our models, and to our business, finding ways to support public servants with cutting-edge AI technologies, and negotiating complex contracts. We'll rely on you to be a thought leader and execution partner to our business and policy teams as part of our rapidly-growing, close-knit commercial function.
Responsibilities:
- Partner with company leaders on strategy and evaluating contracting opportunities, translating the government contracting world for leaders, and translating strategy into contracts
- Craft, negotiate and close complex government contracts, ensuring compliance with federal acquisition regulations (FAR) and agency-specific requirements
- Advise sales and partnerships teams on go-to-market strategies for the government sector, including navigating procurement processes and identifying opportunities
- Advise policy teams on strategic engagements with government agencies and related organizations
- Provide guidance to the business on government contract administration, performance, and compliance matters
- Actively participate in the Commercial Legal Team's scaling and building efforts, and enhance our collegial and supportive team culture
You may be a good fit if you have:
- A JD; active membership in at least one U.S. state bar (California or DC preferred)
- 8+ years of related legal experience (in-house preferred) with at least 5 years of experience developing and negotiating government contracts, research agreements, SaaS agreements, and technology transactions
- Deep knowledge of FAR, DFARS and other government contracting regulations and processes, including OTAs and CRADAs
- Experience advising businesses on selling into the government sector, including strategies for marketing to agencies and winning contracts
- Excellent analytical and communication skills that enable you to effectively support cross-functional teams and interact with government customers
- Intense curiosity about novel technology and science, and an aptitude for learning quickly
- A "doer" attitude, and are willing to roll up your sleeves to support your team and the company
- Strong integrity and empathy, and see these as part of what you bring to your work and work environment
Strong candidates may also have:
- Experience in government service
- Experience supporting emerging technologies in the government space
- Familiarity with intellectual property (patent, trade secret, copyright) issues in government contracts
- Active Secret or Top Secret security clearance
Deadline to apply: None. Applications will be reviewed on a rolling basis.
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time, as needed.
The expected salary range for this position is:
Annual Salary:
$300,000—$375,000 USD
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.
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.