Staff Software Engineer - AI Platform Team

## About the Role As a Staff Software Engineer on the AI Platform team at Coinbase, you will play a critical role in building and operating the Large Language Model (LLM) and agent infrastructure that every team at the company depends on. This is a high-impact role that requires a strong technical background and the ability to lead multi-quarter initiatives. The AI Platform team is part of the Platform group, which is responsible for building and maintaining the core infrastructure that powers Coinbase's products. The AI Platform team owns the company's single path to large language models and the full agent lifecycle, from build to deployment. As a Staff Software Engineer on this team, you will be responsible for leading the design and implementation of core platform systems, including the LLM Gateway, AI Hub, and agent runtime. Coinbase is a remote-first company, which means that you will be working with a distributed team and collaborating with colleagues across different time zones. The company values autonomy and flexibility, and you will be expected to be self-motivated and able to work independently. ## What You Will Do - Own the architecture and delivery of core platform systems, including the LLM Gateway, AI Hub, and agent runtime - Drive the design and implementation of Knowledge Base infrastructure, connecting data sources to auto-provisioned vector and markdown stores queryable by any agent - Lead AI FinOps capabilities, including spend attribution, governance, and cost optimization across all AI workloads company-wide - Partner with engineering, security, legal, finance, product, and external partners to ship high-impact platform capabilities - Build evaluation and observability tooling, including LLM-as-judge harnesses, full tracing, and feedback loops that let subject matter experts refine production agents - Shape applied AI strategy by embedding with teams to build production agents, applying fine-tuning and traditional ML where it outperforms prompting - Lead the development of AI-powered solutions that drive business outcomes and improve customer experiences - Collaborate with cross-functional teams to identify opportunities for AI adoption and drive the implementation of AI-powered solutions - Develop and maintain large-scale AI systems, ensuring scalability, reliability, and performance - Stay up-to-date with the latest developments in AI and machine learning, applying this knowledge to drive innovation and improvement in Coinbase's AI systems ## What We Are Looking For - 8+ years of software engineering experience, with at least 3 years building ML/AI infrastructure, LLM systems, or distributed platform services at scale - Demonstrated ability to lead multi-quarter, Staff-level initiatives end-to-end, from technical design through production operation, with measurable platform-wide impact - Deep expertise in LLM orchestration patterns, agent frameworks, vector databases, and model serving infrastructure across multiple providers - Proven track record of cross-functional partnership with security, legal, and product teams to ship governed, production-grade AI systems - Fluency in Python and at least one systems language (Go, Rust, or C++), with production experience building APIs, microservices, and runtime environments - Utilizes generative AI responsibly, maintaining human oversight to deliver business-ready outputs and drive measurable improvements in workflow efficiency, cost, and quality - Strong understanding of software engineering principles, including design patterns, testing, and deployment - Experience with cloud-based infrastructure and containerization (e.g., Docker, Kubernetes) - Excellent communication and collaboration skills, with the ability to work effectively with remote teams ## Nice to Have - Experience with large-scale data processing and storage systems (e.g., Hadoop, Spark, Cassandra) - Knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn) - Familiarity with agile development methodologies and version control systems (e.g., Git, SVN) - Experience with containerization and orchestration (e.g., Docker, Kubernetes) - Certification in AI, machine learning, or a related field ## Benefits and Perks - Competitive salary and equity package - Comprehensive health insurance, including medical, dental, and vision - Flexible paid time off and holidays - Remote work stipend and equipment budget - Professional development opportunities, including training and conference sponsorships - Access to a diverse and talented team of professionals - Opportunity to work on high-impact projects that drive business outcomes and improve customer experiences - Flexible working hours and autonomy to work from anywhere,

- To stand out as a candidate, be prepared to discuss your experience with AI infrastructure and large language models, and provide specific examples of how you have applied these technologies in previous roles.

• Make sure your resume and online profiles are up-to-date and highlight your technical skills, including programming languages and software engineering principles.
• Be prepared to back up your claims with concrete examples and metrics, and be ready to explain complex technical concepts in simple terms.
• Research the company and the role beforehand, and be prepared to ask informed questions during the interview process.
• Consider building a personal project or contributing to open-source projects that demonstrate your skills and interests in AI and machine learning.
• Be prepared to discuss your approach to responsible AI development and deployment, and how you ensure that your systems are fair, transparent, and accountable.