The primary responsibilities of this role include designing and implementing distributed storage solutions to support scaling data-intensive AI workloads, contributing to the development of exabyte-scale, S3-compatible object storage, and integrating dedicated storage clusters into diverse customer environments. Additionally, the successful candidate will work with technologies such as RDMA, GPU Direct Storage, and distributed filesystems protocols such as NFS or FUSE to optimize storage performance and efficiency.

Key responsibilities also include leading efforts to improve the reliability, durability, security, and observability of our storage stack, collaborating with operations teams to monitor, troubleshoot, and improve storage systems in production environments, setting the bar for developing metrics and dashboards to provide visibility into storage performance and health, analyzing telemetry and system data to drive improvements in throughput, latency, and resilience, and working cross-functionally with platform, product, and infrastructure teams to deliver seamless storage capabilities across the stack.

A key aspect of this role is sharing knowledge and mentoring other engineers on best practices in building distributed, high-performance systems.

To be successful in this role, the ideal candidate will have a strong background in storage systems engineering or infrastructure, with a minimum of 8-10 years of experience. They will also have hands-on experience with object storage or distributed filesystems in production environments, as well as proficiency in a systems programming language such as Go, C, or Rust. Additionally, they will have experience working with cloud-native infrastructure, Kubernetes, and scalable system architectures, and familiarity with storage observability tools and telemetry pipelines.

If you're a motivated and experienced engineer looking to join a dynamic team and contribute to the development of cutting-edge storage solutions, we encourage you to apply for this exciting opportunity.

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At Coinbase, our mission is to increase economic freedom in the world.

We're seeking a Staff Software Engineer to join our Financial Engineering team.

As a Staff Software Engineer, you will be responsible for architecting and building foundational backend systems with a focus on performance, scalability, and reliability.

You will drive strategic technical direction for complex, cross-team initiatives and establish and evolve platform best practices, frameworks, and architectural standards within the team.

You will provide deep technical mentorship, guide design decisions, and raise the bar for engineering quality.

Collaborate with product, finance, and engineering leadership to shape the team's technical roadmap.

Drive system improvements by embedding AI into engineering and operational practices.

What we look for in you:

8+ years building and operating large-scale distributed systems in production.

Deep expertise in backend programming (e.g., Go, Python, Java) and cloud-native architecture.

Proven track record designing highly available, high-performance systems.

Ability to anticipate scaling bottlenecks and take proactive measures.

Experience leading cross-functional technical initiatives and mentoring engineers.

Ability to distill complex technical concepts into clear, actionable solutions.

Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human-in-the-loop practices to deliver business-ready outputs and drive measurable improvements in efficiency, cost, and quality.

Nice to haves:

Experience with financial data, accounting systems, or high-precision transaction processing OR

Experience in the Auth domain.

You’ve worked with Golang, Ruby, Docker, Rails, Postgres, MongoDB or DynamoDB.

You have gone through rapid growth in your company (from startup to mid-size).

Job # : P75025

Pay Transparency Notice: Depending on your work location, the target annual base salary for this position can range as detailed below.

Total compensation may also include equity and bonus eligibility and benefits (including medical, dental, vision and 401(k)).

Annual base salary range (excluding equity and bonus):

$218,025-$256,500 USD

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Anthropic's performance and scaling teams focus on making the most efficient and impactful use of our compute resources, be it inference or training. As an Engineering Manager on these teams, you will be responsible for ensuring you and your team are identifying and removing bottlenecks, building robust and durable solutions, and maximizing the efficiency of our systems. You also will help bring clarity, focus, and context to your teams in a fast-paced, dynamic environment.

Responsibilities:

• Provide front-line leadership of engineering efforts to improve model performance and scale our inference and training systems
• Become familiar with the team's technical stack enough to make targeted contributions as an individual contributor
• Manage day-to-day execution of the team's work
• Prioritize the team's work and manage projects in a highly dynamic, fast-paced environment
• Coach and support your reports in understanding, and pursuing, their professional growth
• Maintain a deep understanding of the team's technical work and its implications for AI safety

You may be a good fit if you:

• Have 1+ years of management experience in a technical environment, particularly performance or distributed systems
• Have a background in machine learning, AI, or a similar related technical field
• Are deeply interested in the potential transformative effects of advanced AI systems and are committed to ensuring their safe development
• Excel at building strong relationships with stakeholders at all levels
• Are a quick learner, capable of understanding and contributing to discussions on complex technical topics
• Have experience managing teams through periods of rapid growth and change
• Are a quick study: this team sits at the intersection of a large number of different complex technical systems that you'll need to understand (at a high level of abstraction) to be effective

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPU/Accelerator programming
• ML framework internals
• OS internals
• Language modeling with transformers

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.

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.

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 policies, and a dynamic and inclusive work environment.

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