{"id":2496574,"url":"https://alion.io/job/binance-binance-accelerator-program-full-stack-engineer-backend-oriented-fully-remote","title":"Binance Accelerator Program - Full Stack Engineer (Backend Oriented) Fully Remote","company":{"id":44,"name":"Binance","domain":"binance.com","url":"https://alion.io/company/binance","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"junior","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":["Hong Kong","Singapore","Australia","Malaysia","New Zealand","Taiwan"],"countries":["HK","SG","AU","MY","NZ","TW"],"hiring_countries":["SG","CN","IN","JP","AU","ID","MY","NZ","PK","PH","KR","TW","TH","VN","AS","BD","BT","BN","KH","CK","TL","FJ","PF","GU","KI","LA","MV","MH","MN","NR","NP","NC","NU","NF","MP","PW","PG","PN","WS","SB"],"hiring_countries_total":47,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Tool Use","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"LlamaIndex","optional":true},{"name":"LLMOps","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Redis","optional":true}],"status":"live","first_seen_at":"2026-10-14T02:04:27Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-15T00:07:18Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"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.\nAbout the TeamBinance AI Pro is building the next generation of AI-native experiences within Binance.\nAt 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.\nAs 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.\nYou will have the opportunity to turn ideas from prototype → benchmark → production, and see your work directly impact how AI Pro behaves at scale.\nResponsibilities\nBuild and improve core components of the Agent Runtime, including intent routing, query rewriting, RAG, tool/skill orchestration, and multi-step agent workflows.\nDesign and optimize Tool Server / Tool Calling capabilities, including tool discovery, execution, result handling, and integration with web search, market data, and internal services.\nDevelop evaluation datasets and evaluation harnesses to measure routing accuracy, answer quality, tool-use performance, and agent reliability.\nInvestigate and improve Agent quality, including failure analysis, regression detection, prompt / workflow optimization, and guardrail effectiveness.\nImprove system observability and reliability through tracing, metrics, logging, dashboards, and production monitoring.\nDebug issues across asynchronous services and agent pipelines, and build integration tests using mocked LLM responses and replayable evaluation cases.\nWork closely with Backend, Data Science, and Algorithm engineers to experiment, benchmark, and bring AI capabilities into production.\nRequirements (Must Have)\nStrong Python/Java programming skills and solid software engineering fundamentals.\nStrong understanding of algorithms, data structures, and problem solving; able to reason about system behavior and trade-offs.\nHands-on experience with LLM applications or Agent systems, through research, coursework, internships, or projects.\nFamiliarity with concepts such as RAG, Tool Calling, Function Calling, Prompting, Agent workflows, or LLM evaluation.\nAble to work comfortably with real codebases, APIs, asynchronous services, testing, CI/CD, and code review.\nStrong debugging and analytical ability, with a mindset of \"understand why it fails, not just make it work.\"\nNice-to-have\nExperience with Agent frameworks such as LangGraph, LangChain, AgentScope, LlamaIndex, or similar.\nExperience with MCP / Tool ecosystems / Agent Runtime.\nExperience building Benchmark / Evaluation / LLM testing infrastructure.\nFamiliarity with vector search, embeddings, RAG evaluation, or LLM observability.\nExperience with Redis, Kafka, Docker, Kubernetes, or cloud-native systems.\nExposure to LLM security, guardrails, prompt-injection defense, or tool-use safety.\nExperience with model inference, latency optimization, or cost optimization.\nWhat You'll Get\nShip real features to a production AI Agent used by Binance users.\nWork on the Agent Runtime and AI infrastructure, rather than only application-layer development.\nLearn from senior Backend, Data Science and Algorithm engineers.\nGain hands-on experience across the modern LLM application stack: Agent Runtime, RAG, Tool Calling, Evaluation, LLMOps and AI Safety.\nOwn meaningful engineering projects end-to-end, from problem definition → implementation → evaluation → production.\nWhy Binance\nShape the future of finance \nCollaborate with world-class talent in a user-centric global organization with a flat structure\nTackle challenging projects in a fast-paced and innovative enviornment with autonomy\nThrive in a results-driven workplace with opportunities for career growth and continuous learning\nCompetitive salary and company benefits\nRemote-first, work-from-home arrangement (may vary depending on the nature of the role and team)\nBinance is committed to being an equal opportunity employer. We believe that having a diverse workforce is fundamental to our success.\nBy submitting a job application, you acknowledge that you have read our Candidate Privacy Notice.\nWe 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. 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