Binance Accelerator Program - Backend Engineer (AI Pro / Agent Infrastructure) Fully Remote

Binance AI Pro is building the next generation of AI-native experiences within Binance.

At the core of AI Pro is an agentic system that can understand user intent, reason through multi-step tasks, retrieve information, call tools, and safely execute actions across Binance's ecosystem.

As a Backend Engineer Intern, you'll work directly on the Agent Runtime and AI infrastructure behind these experiences — from intent routing and tool orchestration to evaluation, observability, and reliability. We're looking for strong technical students who enjoy going deep — people who are excited by LLM Agents, systems, algorithms, and experimentation, and wants to work on real production AI systems alongside experienced Backend, Data Science, and Algorithm engineers.

You will have the opportunity to turn ideas from prototype → benchmark → production, and see your work directly impact how AI Pro behaves at scale.

Strong Python programming skills and solid software engineering fundamentals.

Strong understanding of algorithms, data structures, and problem solving; able to reason about system behavior and trade-offs.

Hands-on experience with LLM applications or Agent systems, through research, coursework, internships, or projects.

Familiarity with concepts such as RAG, Tool Calling, Function Calling, Prompting, Agent workflows, or LLM evaluation.

Able to work comfortably with real codebases, APIs, asynchronous services, testing, CI/CD, and code review.

Strong debugging and analytical ability, with a mindset of "understand why it fails, not just make it work."

Experience with Agent frameworks such as LangGraph, LangChain, AgentScope, LlamaIndex, or similar.

Experience with MCP / Tool ecosystems / Agent Runtime.

Experience building Benchmark / Evaluation / LLM testing infrastructure.

Familiarity with vector search, embeddings, RAG evaluation, or LLM observability.

Experience with Redis, Kafka, Docker, Kubernetes, or cloud-native systems.

Exposure to LLM security, guardrails, prompt-injection defense, or tool-use safety.

Experience with model inference, latency optimization, or cost optimization.

Ship real features to a production AI Agent used by Binance users.

Work on the Agent Runtime and AI infrastructure, rather than only application-layer development.

Learn from senior Backend, Data Science and Algorithm engineers.

Gain hands-on experience across the modern LLM application stack: Agent Runtime, RAG, Tool Calling, Evaluation, LLMOps and AI Safety.

Own meaningful engineering projects end-to-end, from problem definition → implementation → evaluation → production.