Staff Software Engineer, Infrastructure
Company: Interesting Engineering, Inc.
Location: Seattle
Posted on: March 29, 2025
Job Description:
About AnthropicAnthropic'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 RoleAnthropic is seeking talented and
experienced Infrastructure Engineers to join our team and support
the development, scaling, and maintenance of our cutting-edge AI
systems. By joining our Infrastructure team, you will have the
opportunity to work on groundbreaking AI technologies and
contribute to the development of frontier models, supporting
Anthropic's mission to create safe and reliable AI systems that
benefit humanity.We Have Multiple Teams That Are Currently Hiring.
Team Placement Occurs After The Interview Process, Taking Into
Account Your Interests And Experience Alongside Organizational
Needs. This Flexible Approach Allows Us To Match Talented Engineers
With The Infrastructure Teams Where They'll Have The Greatest
Impact And Growth Potential.
- Data Infrastructure: We build and maintain the data systems
powering Anthropic's AI research and products. You'll design and
optimize data pipelines using tools like Spark, Airflow, and dbt
across GCP and AWS. Your work will ensure reliable, scalable data
infrastructure while implementing governance best practices and
driving continuous improvement.
- Core Infrastructure: The systems team is responsible for
supporting some of the largest, most sophisticated clusters in
industry used to train, research, and ultimately serve AI models.
Your work will be crucial in ensuring Anthropic is able to continue
reliably and safely training frontier models. You will be
responsible for building systems and running large Kubernetes
clusters with GPU/TPU/Tranium workloads.
- Runtime Platform: We build and maintain the infrastructure that
monitors the health, performance, and efficiency of our AI systems.
You'll work across teams to implement monitoring solutions using
tools like Prometheus, Splunk, and Grafana, while developing
automated approaches for dashboards and alerts. Your work will
create reliable, low-maintenance systems that enable proactive
monitoring and operational excellence.
- Developer Productivity: The Developer Productivity team enables
Anthropic researchers and engineers to be maximally effective in
securely developing state-of-the-art models, and products that
expose those models to users. All of the code written at Anthropic
goes through systems/infrastructure built and maintained by our
team. We aim to make development at Anthropic secure, efficient,
and delightful.
- Product Infrastructure: The Product Infrastructure team enables
Anthropic's products to achieve best-in-class performance,
reliability, and developer velocity by building and maintaining a
robust, efficient, and scalable product infrastructure stack.
- Cloud Inference: We scale and optimize Claude to serve the
massive audiences of developers and enterprise companies using AWS
and GCP. Our team's engineers are extremely high leverage because
we simultaneously drive two of our company's largest and fastest
growing revenue streams, and we optimize the consumption of one of
our most precious resources: compute. Our team ensures our LLMs
meet rigorous safety, performance, and security standards and
enhance our core infrastructure for packaging, testing, and
deploying inference technology. Your work will increase the scale
at which our services can operate and accelerate our ability to
reliably launch new frontier models and innovative features to
customers across all platforms.Responsibilities
- Lead build out of industry-leading AI clusters (thousands to
hundreds of thousands of machines), partnering closely with cloud
service providers on cluster build out and required features.
- Consult with different stakeholders to deeply understand
infrastructure, data and compute needs, identifying potential
solutions to support frontier research and product
development.
- Set technical strategy and oversee development of high scale,
reliable infrastructure systems.
- Mentor top technical talent.
- Design processes (e.g. postmortem review, incident response,
on-call rotations) that help the team operate effectively and never
fail the same way twice.You May Be a Good Fit If You
- Have 10+ years of relevant industry experience, 3+ years
leading large scale, complex projects or teams as an engineer or
tech lead.
- Are obsessed with distributed systems at scale, infrastructure
reliability, scalability, security, and continuous
improvement.
- Strong proficiency in at least one programming language (e.g.,
Python, Rust, Go, Java).
- Strong problem-solving skills and ability to work
independently.
- Have a passion for supporting internal partners like research
to understand their needs.
- Have excellent communication skills to build consensus with
stakeholders, both internally and externally.
- Possess deep knowledge of modern cloud infrastructure including
Kubernetes, Infrastructure as Code, AWS, and GCP.Strong Candidates
May Also
- Have security and privacy best practice expertise.
- Experience with machine learning infrastructure like GPUs,
TPUs, or Trainium, as well as supporting networking infrastructure
like NCCL.
- Low level systems experience, for example linux kernel tuning
and eBPF.
- Technical expertise: Quickly understanding systems design
tradeoffs, keeping track of rapidly evolving software
systems.Deadline to apply: None. Applications will be reviewed on a
rolling basis.Annual SalaryThe expected salary range for this
position is:$320,000 - $405,000 USD.LogisticsEducation
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
DifferentWe 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.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.
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Keywords: Interesting Engineering, Inc., Seattle , Staff Software Engineer, Infrastructure, IT / Software / Systems , Seattle, Washington
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