Partner with teams across the organization to deeply understand workflows, identify pain points, and uncover high-leverage opportunities for AI automation and efficiency gains. Translate complex business challenges into actionable AI use cases.
Apply advanced GenAI techniques, including large language models (LLMs) and Agentic AI, to rapidly design, build, and iterate on functional prototypes (e.g., AI agents, custom copilots, intelligent workflows) that address business needs. Write high-quality, well-tested code in Python and Golang to support these solutions.
Collaborate with cross-functional teams to evolve prototypes into scalable, secure, production-grade AI solutions aligned with long-term organizational goals.
Provide guidance on AI capabilities, responsible AI usage, prompt engineering best practices, and strategic integration of AI into daily operations. Mentor team members on design principles, coding standards, and AI productivity tools adoption.
Pilot new AI solutions with functional teams, gather feedback, iterate on prototypes, and support adoption to ensure demonstrable value and smooth transitions.
Partner with central AI Platform and DevX teams to leverage existing infrastructure, contribute to shared knowledge bases, and ensure scalability and security of solutions.
Work with Security, Legal, and Compliance teams to ensure all AI solutions adhere to strict security, privacy, and ethical guidelines, especially for sensitive data and high-risk workflows.
Define success metrics, track ROI, and effectively communicate the value delivered by AI initiatives to stakeholders.
Continuously research and experiment with emerging AI models, tools, and industry best practices to bring cutting-edge solutions to Coinbase.

Requirements

5+ years of experience in software engineering, with at least 6 months focused on applied AI, Generative AI, or intelligent automation.
Strong Software Engineering Skills: Proven expertise in designing, building, scaling, and maintaining production services, with a strong understanding of microservices architecture.
Ability to write high-quality, well-tested code that meets customer needs.
Strong technical skills in system design, coding, and debugging complex technical issues to enhance system reliability and scalability.
AI & Automation Skills: Understanding of LLM capabilities, limitations, and architectures (e.g., RAG, agents, fine-tuning concepts).
Hands-on experience with AI tools and platforms (e.g., enterprise LLMs like Gemini/Claude, no-code/low-code automation platforms, agent frameworks LangChain/LangGraph, Python).
Highly analytical and structured problem-solver, comfortable with ambiguity and rapid iteration.
Ability to manage multiple parallel initiatives and prioritize effectively in a fast-paced environment.
Experience working cross-functionally with other engineering and/or non-engineering teams.
Strong understanding of data privacy, security, and ethical considerations related to AI.

Benefits

Bonus eligibility
Equity eligibility
Benefits (including medical, dental, vision and 401(k))

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

PythonGolangAI automationGenerative AIlarge language modelssystem designmicroservices architecturedebuggingscalabilityAI tools

Soft skills

analytical problem-solvingstructured thinkingprioritizationcollaborationmentoringcommunicationadaptabilityfeedback gatheringiterationambiguity management