Pioneer Talent Program - Applied AI Agent/AI Productivity Engineer (Top Talent Program)Active

Binance
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The opportunity

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by over 230 million people in 100+ countries for our industry-leading security, user fund transparency, trading engine…

What you'll do

  • Design and develop AI-powered productivity tools for internal engineering: teams, including coding assistants, knowledge retrieval systems, developer tools and workflow automation.

  • Build and integrate LLM-powered applications for real-world engineering use: cases, such as code generation, code understanding, testing and developer workflow automation.

  • Develop AI Agent workflows and supporting infrastructure , including tool: calling, context management, memory, evaluation and workflow orchestration.

  • Integrate AI capabilities into the software development lifecycle, from: requirements and development to testing and deployment, to improve engineering productivity.

  • Work closely with engineering teams to identify development bottlenecks and: translate them into practical AI-driven solutions .

  • Apply approaches such as Prompt Engineering, RAG, AI Agents and MCP/tool: calling , and continuously evaluate emerging AI technologies for practical adoption.

What they're looking for

  • Bachelor's degree or above in Computer Science, Data Science, Software Engineering or a related field .
  • –5 years of software engineering or applied AI engineering experience.
  • Proficient in at least one programming language, such as Python, Java, Go or JavaScript/TypeScript .
  • Solid software engineering fundamentals, including API integration, system design, debugging and testing .
  • Hands-on experience building or integrating LLM-powered applications .
  • Practical understanding of one or more of LLM Agents, RAG, Prompt: Engineering, MCP/tool calling, context management or AI evaluation .
  • Experience with backend, platform or full-stack development and integrating: AI capabilities into production or internal workflows.
  • Strong problem-solving and learning ability, with a hands-on and proactive approach .