Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
API @ 6
AWS @ 7
Agentic AI @ 4
Audit @ 4
Compliance @ 4
Distributed Systems @ 4
GenAI
Generative AI @ 6
Go @ 6
GraphQL @ 6
Kafka @ 7
Kubernetes @ 7
LLM @ 4
Memcached @ 7
Mentoring
Microservices @ 6
NoSQL @ 7
Observability
Python @ 6
RAG @ 4
Redis @ 7
SQL @ 7
Security @ 4
Terraform @ 7
gRPC @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Coinbase is a remote-first, but not remote-only company. Employees are expected to meet quarterly for in-person working sessions called “surges.”
The Customer Administration Engineering team is responsible for building and operating secure, foundational platforms that power customer data operations across Coinbase. Its flagship product, Control Center, is a secure system of action for approximately 7,000 internal users across Customer Experience, Compliance, Legal, Global Investigations, Trust and Risk, and other teams. The platform also supports internal tools and AI automation through backend APIs and MCP. The team is evolving Control Center from a specialist user interface into a modular, AI-agent-ready operations platform.
As a Staff Software Engineer, you will serve as a technical anchor for the team by driving architectural decisions, mentoring engineers, and leading the delivery of high-impact, cross-cutting platform capabilities.
Responsibilities
- Architect and deliver foundational platform capabilities, including MCP tool registries, AI orchestration layers, risk-based access automation, and an away-team contribution model that enables product groups to build safely and efficiently on the platform.
- Evolve Control Center into an AI-agent-ready, headless operations platform.
- Design and implement MCP procedure constructs, agentic guardrails, human-in-the-loop orchestration, and evaluation frameworks for securely executing sensitive customer operations with human and autonomous AI agents.
- Partner with Engineering Managers and Product counterparts to define architectural roadmaps, author technical design documents, lead design reviews, decompose complex initiatives into milestones, and improve engineering quality through code review and mentorship.
- Build and maintain reliable, secure, distributed backend services, including SLO definition, observability instrumentation, incident response, and operational readiness for Tier-1 platform systems.
- Collaborate with Enterprise Applications and Architecture engineering teams, Product Engineering, and Security Engineering to deliver cross-functional outcomes and shared platform primitives.
Requirements
- 8+ years of hands-on software engineering experience.
- Demonstrated experience architecting and delivering large-scale, high-traffic distributed systems in production.
- Deep proficiency in backend service design, API development using gRPC, MCP, and GraphQL, and scalable microservices architectures.
- Ability to independently lead ambiguous, high-impact technical initiatives from design through production.
- Experience writing high-quality, well-tested code and setting engineering standards across complex, multi-team problem spaces.
- Strong experience with cloud-native infrastructure and modern backend technologies, including AWS, Kubernetes, Terraform, BuildKite or CircleCI, Kafka or MQ, Redis or Memcached, and SQL and/or NoSQL databases.
- Experience building or integrating secure, compliant internal tools or platforms, with an understanding of security controls, access management, audit logging, data governance, and engineering practices in regulated financial services environments.
- Experience building or integrating agentic AI systems, including MCP servers, LLM orchestration layers, RAG pipelines, human-in-the-loop workflows, or evaluation and guardrail frameworks for production agentic workloads.
- Proficiency in Go (Golang) as a primary backend language, with willingness to work with Python where applicable in the AI stack.
- Ability to use generative AI responsibly, maintaining human oversight while delivering business-ready outputs and improving workflow efficiency, cost, and quality.
Compensation
The annual base salary range, excluding equity and bonus, is ₹9,424,500–₹9,424,500 INR. Total compensation may also include equity, bonus eligibility, and medical, dental, and vision benefits.
Candidates may submit a maximum of three applications within a six-month period. Coinbase is an equal opportunity employer.