Staff Software Engineer (Policies Platform - Identity)
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Job description
We're hiring a Staff Software Engineer to be the technical anchor for the Policies Platform - Coinbase's foundational engine for policy management, decisioning, and authorization. As a Staff Engineer on the Policies Platform, you'll be a technical anchor for one of Coinbase's most critical infrastructure teams. You'll set the technical direction for the platform's evolution, leading the shift to an AI-native, self-serve policy engine while building alignment across engineering, compliance, legal, and product teams. Your decisions will shape how dozens of engineering teams across Coinbase author, deploy, and trust compliance logic at scale. The Policies Platform powers policy management, decisioning, and authorization across 20+ domains and 40+ dependent services, handling millions of requests per minute. This role requires someone who can operate in ambiguity, drive clarity, and build systems that create leverage far beyond any single team.
What you'll be doing:
- Own the technical strategy and architecture for the Policies Platform - including the AI-native policy authoring system, Policy Framework v2, edge authorization, and the self-serve developer experience.
- Define and drive the technical roadmap, making deliberate tradeoffs between speed, reliability, and long-term scalability as the platform expands to support new Coinbase products and international regulatory requirements.
- Lead the most ambiguous, highest-risk initiatives on the team - including AI-powered impact simulation before policy changes ship, AI chatbot for compliance self-service, and embedding authorization into API gateway-level signed tokens.
- Secure cross-team alignment and commitment - working with 20+ dependent domain teams, regulatory/compliance stakeholders, and engineering leadership to drive adoption of new platform standards and patterns.
- Define engineering processes and quality practices - from code review standards for policy-as-code, to CI/CD pipeline requirements for automated load and regression testing.
- Maintain high technical output while simultaneously elevating the capabilities of the broader team - you lead by doing, not just advising.
- Contribute to org-wide initiatives including OKR planning, technical prioritization, and long-term platform strategy in partnership with engineering leadership.
Requirements
- 8+ years of software engineering experience, with a track record of architecting and delivering systems at scale - high-throughput, high-availability services serving millions of requests in production.
- Proven experience leading AI/LLM product development - building AI agents, code generation systems, or developer-facing AI tooling in production environments.
- Strong command of Go, gRPC, Kubernetes, and service mesh architectures.
- Ability to drive technical clarity in ambiguous, high-stakes situations - you can take a vague problem ("compliance teams can't self-serve"), define the right solution space, and execute it to completion.
- A history of influencing across organizational boundaries - getting buy-in from skeptical stakeholders, aligning competing priorities, and building durable cross-team partnerships.
- Excellent written and verbal communication - you produce technical design documents that build organizational confidence and create shared understanding.
- Remote-friendly with on-site presence at either the San Francisco or New York City office approximately once per week for architecture reviews, stakeholder meetings, and team offsites
- 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
- Expertise in authorization and policy systems (OPA, Cedar, Zanzibar-inspired systems, or equivalent) - or equivalent infrastructure platform expertise with willingness to develop deep policy domain knowledge.
- Experience building AI-native developer platforms.
- Familiarity with regulatory compliance engineering (financial services, KYC/AML, MiCA, or equivalent).
- Background in policy-as-code, GitOps, or automation at scale.
- Prior experience in open source policy or authorization ecosystems (OPA, OpenFGA, Casbin).
- Experience defining platform adoption strategies - including self-serve onboarding, documentation, and developer evangelism.