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

Binance
Hong Kong +1 more
Remote

Who this role is best for

Strong fit for candidates with applied AI engineering experience who build AI-powered productivity tools and integrate LLMs into engineering workflows, particularly those familiar with backend or full-stack development and working in a remote-first, collaborative environment.

Best fit for

  • Candidates with 1–5 years of applied AI engineering experience building LLM-powered tools for internal teams
    — “1–5 years of software engineering or applied AI engineering experience”
  • Individuals who have hands-on experience integrating AI into real-world engineering processes and workflows
    — “Integrate AI capabilities into the software development lifecycle, from requirements and development to testing and deployment”
  • Candidates with a background in backend, platform, or full-stack development and AI tooling integration
    — “Experience with backend, platform or full-stack development and integrating AI capabilities into production or internal workflows”

How to stand out

  • Highlight end-to-end project ownership and AI integration into software development workflows
    — “Own projects end-to-end, from problem definition and technical design to implementation, deployment and iteration”
  • Emphasize experience with AI Agent frameworks, tool calling, and context management in your resume and interview responses
    — “Experience with AI Agent frameworks, Agent memory, tool orchestration or multi-agent systems”
  • Showcase contributions to open-source projects or a GitHub portfolio demonstrating AI tooling or productivity software development
    — “Open-source contributions or an active GitHub portfolio”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • design and develop AI-powered productivity tools
  • integrate AI capabilities into the software development lifecycle
Typical background
Bachelor's degree in Computer Science, Data Science, Software Engineering1-5 years of software engineering or applied AI engineering experience

Skills & requirements

Required

Software EngineeringLlm-powered ApplicationsPrompt EngineeringRAGAI AgentsMcp/tool CallingBackend Development

Preferred

LangchainClaude Agent SDKMCPOpen-source Contributions

Stack & domain

PythonJavaGoJavaScriptTypeScriptAPI IntegrationSystem DesignDebuggingTestingLlm-powered ApplicationsPrompt EngineeringRAGAI AgentsMcp/tool CallingContext ManagementBackendPlatformFull-stack DevelopmentDevOpsCI/CDCloud InfrastructureEngineering AutomationLangchainClaude Agent SDKMCPCommunicationCollaborationProblem-solvingLearning AbilityProactive ApproachFinanceBlockchainCryptocurrencyAILLMCoding AssistantsKnowledge Retrieval SystemsDeveloper ToolsWorkflow Automation

About the role

Original posting from Binance via Greenhouse

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, and more. Our mission is to increase the freedom of money and financial access for people around the world.

Responsibilities:

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.

Own projects end-to-end, from problem definition and technical design to implementation, deployment and iteration.

Requirements

Bachelor's degree or above in Computer Science, Data Science, Software Engineering or a related field.

1–5 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.

Good communication and collaboration skills, with the ability to work closely with engineering teams to understand and solve real-world problems.

Bonus Points

Experience building AI productivity tools, developer tools, internal platforms or workflow automation systems.

Experience with AI Agent frameworks, Agent memory, tool orchestration or multi-agent systems.

Experience integrating LLMs into software development workflows, such as coding, testing, code review or deployment.

Experience with RAG, knowledge systems, search or documentation platforms.

Exposure to DevOps, CI/CD, cloud infrastructure or engineering automation.

Experience with LangChain, Claude Agent SDK, MCP or similar AI tooling.

Open-source contributions or an active GitHub portfolio.

Why Binance

Shape the future of finance 

Collaborate with world-class talent in a user-centric global organization with a flat structure

Tackle challenging projects in a fast-paced and innovative enviornment with autonomy

Thrive in a results-driven workplace with opportunities for career growth and continuous learning

Competitive salary and company benefits

Remote-first, work-from-home arrangement (may vary depending on the nature of the role and team)

Binance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.

By submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Source: Binance careers (Greenhouse)

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