At a Glance
- Tasks: Lead the development of reliable AI infrastructure and manage complex technical initiatives.
- Company: Join a pioneering AI company focused on building safe and scalable systems.
- Benefits: Competitive salary, visa sponsorship, hybrid work model, and opportunities for professional growth.
- Other info: Dynamic team environment with mentorship opportunities and a focus on innovation.
- Why this job: Make a real impact in AI by shaping the future of infrastructure technology.
- Qualifications: 8+ years in software engineering with expertise in distributed systems and cloud platforms.
The predicted salary is between 80000 - 100000 € per year.
Requirements
- Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
- Strong proficiency in at least one systems language (e.g., Rust, Go, or Python) and IaC proficiency with Terraform
- Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
- Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
- Ability to build alignment across senior stakeholders and communicate effectively at all levels
- (Desirable) 8+ years of software engineering experience, including time as a technical lead setting direction for a team
- (Desirable) Experience managing large scale compute infrastructure at hyperscale (10K+ nodes), including capacity management and efficiency
- (Desirable) Depth in one or more of: Kubernetes internals (scheduler, autoscaler, kubelet, Karpenter), cluster orchestration systems (Mesos, Borg-like), or node provisioning pipelines
- (Desirable) Low-level systems experience: kernel, virtualization, device drivers, firmware, or hardware health/diagnostics daemons
- (Desirable) Familiarity with high-performance networking (EFA, RDMA, InfiniBand) for distributed ML workloads
- (Desirable) Demonstrated ownership of production reliability for high-throughput, latency-sensitive systems
- (Desirable) Contributions to relevant open-source projects (Kubernetes, Linux kernel, container runtimes, etc.)
- (Desirable) Skill in quickly understanding systems design tradeoffs and keeping track of rapidly evolving software systems
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
- 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
What the job involves
Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable. The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand.
Node Infra owns the full lifecycle of accelerator capacity at Anthropic. We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research.
- Own the technical strategy and roadmap for node lifecycle management – ingestion, bring‑up, health checking, and automated repair
- Drive cross‑team initiatives to build and scale AI clusters across multiple clouds and accelerator families
- Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
- Define infrastructure architecture, ensuring the hardest problems get solved – whether by you directly or by working through others
- Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
- Establish and evolve operational excellence practices (incident response, post‑mortem culture, on‑call)
- Support the growth of engineers around you through technical mentorship and coaching
Staff Software Engineer (Node Infrastructure) employer: Deepstreamtech
At Anthropic, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. Our commitment to employee growth is evident through our mentorship programmes and opportunities to lead complex technical initiatives, all while working in a hybrid environment that values flexibility. Located in a vibrant tech hub, we offer competitive benefits and the chance to contribute to cutting-edge AI infrastructure, making your work both meaningful and rewarding.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Engineer (Node Infrastructure)
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, conferences, or even online webinars. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to distributed systems or cloud platforms. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts clearly and concisely, as you'll need to communicate effectively with senior stakeholders. Mock interviews can be super helpful!
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications come in directly. Plus, it shows you're genuinely interested in joining our team. Remember, even if you don't tick every box, we encourage you to throw your hat in the ring!
We think you need these skills to ace Staff Software Engineer (Node Infrastructure)
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your deep expertise in distributed systems and cloud platforms. We want to see your hands-on experience with Kubernetes, IaC, and any relevant systems languages like Rust or Go. Don’t hold back on showcasing your technical prowess!
Tailor Your Application:Customise your application to reflect the job description. Use keywords from the listing to demonstrate that you understand what we’re looking for. This helps us see how your experience aligns with our needs at StudySmarter.
Share Your Achievements:Don’t forget to mention any complex initiatives you've led or significant contributions to open-source projects. We love seeing a track record of ownership and reliability in high-throughput systems, so make sure to include those details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we’re excited to see what you bring to the table!
How to prepare for a job interview at Deepstreamtech
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of distributed systems, cloud platforms, and the specific technologies mentioned in the job description. Be ready to discuss your hands-on experience with Kubernetes, IaC, and any machine learning accelerators you've worked with. This will show that you’re not just familiar with the tools but can also apply them effectively.
✨Showcase Your Leadership Skills
Since the role involves leading complex initiatives, prepare examples from your past where you’ve successfully led a team or project. Highlight how you built alignment across stakeholders and communicated effectively at all levels. This will demonstrate your ability to take charge and guide others towards a common goal.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions during the interview. Be ready to explain your thought process on systems design trade-offs and how you’ve tackled challenges in large-scale compute infrastructure. Practising explaining complex concepts clearly will help you stand out as a candidate who can bridge the gap between technical and non-technical audiences.
✨Emphasise Your Problem-Solving Approach
The role requires a knack for diagnosing and resolving issues in high-throughput systems. Prepare to discuss specific instances where you’ve identified problems and implemented solutions, especially in production environments. This will showcase your ownership of production reliability and your proactive approach to maintaining system health.
