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# Senior Software Engineer, Backend - Platform (Core AI Automation)

- **Company:** Coinbase, Inc.
- **Location:** Topeka, KS, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Code Review, Software Design Patterns, Python (Programming Language), Software Deployment, Software Engineering, Large Language Models, Prompt Engineering, Generative AI, Backend, Machine Learning Operations, Data Pipelines, Golang, Microservices
- **Published:** August 7, 2026
- **Apply:** https://www.kansasworks.com/jobs/13633912

## About the Role

* 5+ years of experience in software engineering, with proven expertise in designing, building, and maintaining production services using a microservices architecture.

 * Hands-on experience building LLM-based applications or AI/ML systems in production, including prompt engineering, retrieval-augmented generation (RAG), or agentic AI frameworks.

 * Proficiency in Python and Golang (or comparable backend languages), with experience integrating third-party AI models and APIs into production workflows.

 * Track record of delivering end-to-end projects with measurable business impact in ambiguous problem spaces.

 * Experience building data pipelines, integrating with external vendors, or working with large-scale unstructured data sources (e

## Description

* Own the design and delivery of agentic AI systems that power Coinbase's customer support and compliance automation, from LLM orchestration through production deployment and monitoring.

 * Build scalable, secure backend infrastructure in Python and Golang that serves AI workloads, including model integration pipelines, guardrails, grounding mechanisms, and measurement frameworks.

 * Drive end-to-end project execution on complex AI initiatives, making technical trade-offs across latency, accuracy, cost, and reliability.

 * Partner with Customer Experience, Compliance, and product engineering teams to identify high-impact automation opportunities and translate operational pain points into AI-powered solutions.

 * Strengthen engineering quality across the team by leading code reviews, mentoring engineers on AI system design patterns, and contributing to on-call rotations and incident response.


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