Software Engineer, Technical Partnerships

To be a strong candidate for the Software Engineer, Technical Partnerships role at Anthropic, you should have 5-15+ years of experience in software engineering, specifically in building and operating mission-critical backend systems. Proficiency in coding, particularly in Python, and an understanding of complex distributed systems is essential. Additionally, familiarity with AI accelerator technologies and a customer-focused mindset are crucial.

As a Software Engineer in the Technical Partnerships team at Anthropic, you'll focus on optimizing cloud service integrations for our large language models and APIs. This includes designing and implementing features, enhancing infrastructure, and ensuring the performance and reliability of services across third-party platforms.

This role can be based in either San Francisco, CA, or Seattle, WA. Anthropic offers a hybrid working policy, requiring staff to be in the office at least 25% of the time to foster collaboration and teamwork.

Anthropic aims to create AI systems that are reliable, interpretable, and steerable, ensuring safety and benefit for users and society. The Software Engineer, Technical Partnerships will directly contribute to this mission by enhancing the infrastructure that supports these AI systems.

Anthropic provides competitive compensation packages, generous vacation and parental leave policies, options for equity donation matching, flexible working hours, and an inviting office environment designed for collaboration. These benefits support both professional and personal growth.

Yes, Anthropic does sponsor work visas for the Software Engineer, Technical Partnerships position. While not every role is eligible, the company strives to ensure that candidates receive the necessary support during the visa application process.

Candidates for the Software Engineer, Technical Partnerships position should ideally have experience with coding languages like Python, as well as tools like Kubernetes, Docker, and containerization technologies. Familiarity with platform services on AWS or GCP and direct customer interaction during product deployment can also be advantageous.

When designing scalable backend systems, I focus on modular architecture, ensuring each component can be independently scaled. I prioritize using asynchronous processing techniques and efficient data storage solutions that can handle increasing loads without compromising performance.

In my previous roles, I've developed and managed RESTful APIs, prioritizing design consistency and performance optimization. I ensure thorough documentation and testing, aligning features closely with customer needs to create a seamless integration experience.

AI safety is paramount in my practices; I ensure that our models are trained with ethical considerations in mind, regularly auditing and testing them for biases and vulnerabilities. I collaborate with cross-functional teams to incorporate safety checks at every stage of development.

I employ techniques such as monitoring application performance metrics, leveraging auto-scaling features, and conducting regular load testing to understand peak demands. This helps in planning capacity and optimizing the allocation of cloud resources effectively.

In collaborating with external teams, I emphasize clear communication and regular updates on project progress. Establishing shared goals and documentation can significantly ease coordination and ensure that everyone is aligned throughout the partnership.

In my last project, I implemented a monitoring system with alerts for key performance indicators, allowing the team to proactively address issues before they impacted users. This system also included automatic failover mechanisms, which enhanced overall reliability.

I'm experienced in using Docker to containerize applications, which enhances the deployment process and ensures consistency across environments. I also have worked with Kubernetes for orchestration, maintaining scalable applications seamlessly.

My approach to incident management involves establishing a clear incident response plan that includes communication protocols, task delegation, and post-mortems to learn from each incident. Being calm and methodical helps in resolving issues quickly and effectively.

To maintain observability, I integrate logging, monitoring, and tracing frameworks into the architecture. I design dashboards that reflect real-time system health and performance, providing insights that help in diagnosing issues swiftly.

I stay updated on the latest developments in the AI field by engaging with community forums, attending conferences, and continuously learning through online courses. Collaborating with peers also helps me gain diverse perspectives on emerging trends.