[Hiring] Binance Accelerator Program - AI Backend Engineer @Binance

Role Description

Binance Accelerator Program (BAP) is a 3-6 month internship program designed for Early Career talent to have firsthand experience in the rapidly expanding digital assets space. You will be given the opportunity to develop your skills at Binance and understand what it’s like to work at the world's leading blockchain ecosystem. As part of your internship in the BAP, there will also be opportunities for networking and development, which will expand your professional network and build transferable skills to propel you forward in your career.

What you'll do

• Build and improve pieces of the agent runtime: intent routing, query rewrite, RAG/FAQ answering, tool/skill orchestration (L0–L6 loop).
• Extend the Tool Server — add and optimize tools (web search, market data, report APIs), improve tool-call efficiency and output quality.
• Strengthen evaluation: write eval datasets and harnesses, measure intent-routing accuracy and answer quality, catch regressions before release.
• Improve observability: traces, metrics, logging (Opik/Pinpoint), production dashboards and alerts.
• Fix bugs across the pipeline (routing, skill loading, guardrail false-triggers) and write integration tests with mock-LLM cassette replay.

Qualifications

• Solid Python and clean coding habits; comfortable in a real service codebase with CI, code review, and typing.
• Understanding of LLM application basics — prompting, RAG, tool/function calling, or agent frameworks (from coursework, projects, or internships).
• Able to reason about correctness and write tests; debug across async/services.
• Available for a sustained internship and eager to iterate quickly on feedback.

Requirements

• Experience with an agent framework (AgentScope / LangChain / LlamaIndex or similar) is a nice-to-have.
• Familiarity with vector search / embeddings, evaluation frameworks (Opik, ragas), or LLM observability is a nice-to-have.
• Exposure to Kafka, Redis/Lindorm, S3, config systems (Apollo), or Docker/K8s is a nice-to-have.
• Interest in evaluation, guardrails/safety (prompt-attack defense), or latency/cost optimization is a nice-to-have.

Benefits

• Ship real features into a production AI agent used across the app.
• Mentorship from senior BE/DS/algo engineers; end-to-end ownership of scoped tasks.
• Hands-on exposure to the full modern LLM-app stack: RAG, tool servers, evals, LLMOps.
• Competitive salary and company benefits.
• Work-from-home arrangement (the arrangement may vary depending on the work nature of the business team).