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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and deploying AI-powered systems, with a strong focus on machine learning, large language models, and multi-agent frameworks. Proven ability to manage complex ML initiatives and communicate effectively with cross-functional teams.
Highest-signal resume keywords
Machine Learning ExpertiseLarge Language ModelsPython ProficiencyMulti-Agent Systems DevelopmentGenerative AI Tools
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningSoftware EngineeringDeep Learning ArchitecturesNatural Language ProcessingInformation RetrievalConversational AIStatistical ModelingTechnical Design DocumentationHuman-in-the-Loop PracticesProduction-Grade ML Services
Soft Skills
Communication SkillsMentoringCross-Functional CollaborationPrioritizationTechnical Trade-Off Management
Tools & Technologies
LangGraphLangSmithGoogle ADKVertex AIAWS BedrockLibreChatGeminiGlean
Industry Keywords
AI-Powered SystemsAgent AssistAutomated ResolutionAdversarial Input ManagementML/AI Evaluation Frameworks
Tech Stack
Tools & technologiesAWSPython
About the role
Key responsibilities & impact- Design and build AI-powered systems connecting Coinbase’s Help Center, chatbots, and agent workflows
- Architect and deploy a scalable multi-agent framework for agent assist, internal SOP execution, and secure LLM-powered actions
- Own end-to-end execution of complex ML initiatives from design through production delivery
- Manage priorities, technical trade-offs, and cross-functional dependencies
- Build and optimize AI-driven concierge chat and agent copilot experiences
- Improve automated resolution rates and reduce case handling time
- Develop systems to detect and manage bad actors and adversarial inputs
- Establish best practices for system design, coding standards, and ML/AI evaluation frameworks
- Mentor team members on architectural decisions and modern ML development workflows
- Partner with Conversation Design, CX, and Engineering teams to deliver secure, compliant, and scalable AI support
Requirements
What you’ll need- 5+ years of professional experience in machine learning and software engineering
- Track record of shipping production-grade ML services at scale
- Hands-on expertise with large language models, deep learning architectures, and the generative AI ecosystem, including LangGraph, LangSmith, Google ADK, Vertex AI, or AWS Bedrock
- Ability to build multi-agent or LLM orchestration systems
- Proficiency in Python
- Specialized depth in at least one domain: NLP, information retrieval, conversational AI, or advanced statistical modeling
- Ability to ramp quickly on adjacent domains
- Ability to write technical design documents
- Ability to communicate complex ML concepts clearly to non-technical stakeholders
- Responsible use of generative AI tools and copilots such as LibreChat, Gemini, or Glean
- Ability to apply human-in-the-loop practices and deliver business-ready outputs
Benefits
Comp & perks- Equity eligibility
- Bonus eligibility
- Medical insurance
- Dental insurance
- Vision insurance
- 401(k)
- Quarterly in-person working sessions called “surges”
- Reasonable accommodations for individuals with disabilities
- Free compatible screen reader for applicants needing screen reading technology