LikeRemoteBinance Accelerator Program - Backend Engineer (AI Pro / Agent Infrastructure)
🇮🇳 India | 🇸🇬 Singapore | 🇯🇵 Japan | 🇹🇭 Thailand | 🇨🇳 China | 🇮🇩 Indonesia | 🇧🇩 Bangladesh | 🇮🇷 Iran | 🇯🇴 Jordan | 🇰🇿 Kazakhstan | 🇲🇾 Malaysia | 🇳🇵 Nepal | 🇵🇰 Pakistan | 🇵🇭 Philippines | 🇰🇷 South Korea | 🇱🇰 Sri Lanka | 🇹🇼 Taiwan | 🇹🇷 Turkey | 🇻🇳 Vietnam | 🇱🇧 Lebanon | 🇲🇲 Myanmar | 🇱🇦 Laos | 🇾🇪 Yemen | 🇲🇻 Maldives | 🇴🇲 Oman
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Binance Accelerator Program - Backend Engineer (AI Pro / Agent Infrastructure)
from 🇮🇳 India | 🇸🇬 Singapore | 🇯🇵 Japan | 🇹🇭 Thailand | 🇨🇳 China | 🇮🇩 Indonesia | 🇧🇩 Bangladesh | 🇮🇷 Iran | 🇯🇴 Jordan | 🇰🇿 Kazakhstan | 🇲🇾 Malaysia | 🇳🇵 Nepal | 🇵🇰 Pakistan | 🇵🇭 Philippines | 🇰🇷 South Korea | 🇱🇰 Sri Lanka | 🇹🇼 Taiwan | 🇹🇷 Turkey | 🇻🇳 Vietnam | 🇱🇧 Lebanon | 🇲🇲 Myanmar | 🇱🇦 Laos | 🇾🇪 Yemen | 🇲🇻 Maldives | 🇴🇲 Oman
About the Team
Binance AI Pro is building the next generation of AI-native experiences within Binance.
At the core of AI Pro is anagentic system that can understand user intent, reason through multi-step tasks, retrieve information, call tools, and safely execute actions across Binance's ecosystem.
As aBackend Engineer Intern, you'll work directly on theAgent Runtime and AI infrastructure behind these experiences — from intent routing and tool orchestration to evaluation, observability, and reliability. We're looking forstrong 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.
Responsibilities
- Build and improve core components of theAgent Runtime, including intent routing, query rewriting, RAG, tool/skill orchestration, and multi-step agent workflows.
- Design and optimizeTool Server / Tool Calling capabilities, including tool discovery, execution, result handling, and integration with web search, market data, and internal services.
- Developevaluation datasets and evaluation harnesses to measure routing accuracy, answer quality, tool-use performance, and agent reliability.
- Investigate and improveAgent quality, including failure analysis, regression detection, prompt / workflow optimization, and guardrail effectiveness.
- Improve systemobservability and reliability through tracing, metrics, logging, dashboards, and production monitoring.
- Debug issues across asynchronous services and agent pipelines, and build integration tests using mocked LLM responses and replayable evaluation cases.
- Work closely withBackend, Data Science, and Algorithm engineers to experiment, benchmark, and bring AI capabilities into production.
Requirements (Must Have)
- StrongPython programming skills and solid software engineering fundamentals.
- Strong understanding ofalgorithms, data structures, and problem solving; able to reason about system behavior and trade-offs.
- Hands-on experience withLLM applications or Agent systems, through research, coursework, internships, or projects.
- Familiarity with concepts such asRAG, 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."
Nice-to-have
- Experience withAgent frameworks such as LangGraph, LangChain, AgentScope, LlamaIndex, or similar.
- Experience withMCP / Tool ecosystems / Agent Runtime.
- Experience buildingBenchmark / Evaluation / LLM testing infrastructure.
- Familiarity withvector search, embeddings, RAG evaluation, or LLM observability.
- Experience withRedis, Kafka, Docker, Kubernetes, or cloud-native systems.
- Exposure toLLM security, guardrails, prompt-injection defense, or tool-use safety.
- Experience withmodel inference, latency optimization, or cost optimization.
What You'll Get
- Ship real features to a production AI Agent used by Binance users.
- Work on theAgent Runtime and AI infrastructure, rather than only application-layer development.
- Learn from seniorBackend, Data Science and Algorithm engineers.
- Gain hands-on experience across the modernLLM application stack: Agent Runtime, RAG, Tool Calling, Evaluation, LLMOps and AI Safety.
- Own meaningful engineering projects end-to-end, fromproblem definition → implementation → evaluation → production.
