Senior Software Engineer – AI Platform

Coinbase

Senior Software Engineer building Coinbase’s LLM Gateway, agent runtime, knowledge bases, and AI FinOps platform. Leading scalable, governed AI infrastructure across engineering, security, legal, finance, and product teams.

Posted 8/6/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $186,065 - $218,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing ML/AI infrastructure, particularly in LLM systems and distributed platform services. Proven ability to lead cross-functional initiatives and implement production-grade AI solutions with a focus on governance and cost optimization.

Highest-signal resume keywords

LLM Orchestration PatternsPython ProgrammingMicroservices DevelopmentAI FinOps CapabilitiesVector Databases

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning InfrastructureLLM SystemsDistributed Platform ServicesAPI DevelopmentModel Serving Infrastructure

Soft Skills

Cross-Functional CollaborationLeadership

Tools & Technologies

MicroVM SandboxesGoverned MCP GatewayEvaluation ToolingObservability Tooling

Industry Keywords

Generative AICost OptimizationProduction-Grade AI SystemsData Sources Integration

Tech Stack

Tools & technologies

CloudGoMicroservicesPythonRust

About the role

Key responsibilities & impact

Own the architecture and delivery of core platform systems including the LLM Gateway, AI Hub, and agent runtime with microVM sandboxes and governed MCP gateway
Design and implement Knowledge Base infrastructure connecting data sources to auto-provisioned vector and markdown stores
Lead AI FinOps capabilities including spend attribution, governance, and cost optimization across company-wide AI workloads
Partner with engineering, security, legal, finance, product, frontier labs, and major cloud providers
Build evaluation and observability tooling including LLM-as-judge harnesses, tracing, and feedback loops
Shape applied AI strategy by embedding with teams to build production agents and applying fine-tuning or traditional ML where appropriate

Requirements

What you’ll need

5+ years of software engineering experience building ML/AI infrastructure, LLM systems, or distributed platform services at scale
Ability to lead multi-quarter initiatives 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
Experience partnering cross-functionally 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++
Production experience building APIs, microservices, and runtime environments
Responsible use of generative AI with human oversight and measurable workflow, cost, and quality improvements

Benefits

Comp & perks

Equity and bonus eligibility
Medical, dental, and vision benefits
401(k)
Remote-first work arrangement
Quarterly in-person working sessions (“surges”)
Reasonable accommodations for individuals with disabilities