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 an experienced Engineering Manager to join our Inference Scalability and Capability team. This team is responsible for building and maintaining the critical systems that serve our LLMs to a diverse set of consumers. As the cornerstone of our service delivery, the team focuses on scaling inference systems, ensuring reliability, optimizing compute resource efficiency, and developing new inference capabilities. The team tackles complex distributed systems challenges across our entire inference stack, from optimal request routing to efficient prompt caching.
Responsibilities:
- Build and lead a high-performing team of engineers through technical mentorship, strategic hiring, and creating an environment that fosters innovation
- Drive operational excellence of inference systems (deployments, auto-scaling, request routing, monitoring) across cloud providers
- Facilitate development of advanced inference features (e.g., prompt caching, constrained sampling, fine-tuning)
- Partner deeply with research teams to productionize new models, infrastructure teams to optimize hardware utilization, and product teams to deliver customer-facing features
- Create clear technical roadmaps and execution strategies in a fast-moving environment while managing competing priorities
You may be a good fit if you:
- Have 5+ years of experience leading large-scale distributed systems teams
- Have excellence in building high-trust environments and helping teams navigate technical uncertainty while maintaining velocity
- Exhibit demonstrated ability to recruit, scale, and retain engineering talent
- Possess outstanding communication and leadership skills
- Show a deep commitment to advancing AI capabilities responsibly
- Have a strong technical background enabling you to make architectural decisions and guide technical direction
Strong candidates may also have experience with:
- Implementing and deploying machine learning systems at scale
- LLM inference optimization including batching and caching strategies
- Cloud-native architectures, containerization, and deployment across multiple cloud providers
- High-performance computing environments and hardware acceleration (GPU, TPU, Trn)
**Deadline to apply: **None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$320,000—$405,000 USD
Logistics
**Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.